Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2019
Forfattere
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 ClearySammendrag
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Sammendrag
Little attention has been paid to the effects of personality traits on the consumption of wine and beer. We used a survey to investigate the associations between personality traits and the differences in expected consumption frequencies of wine and beer for 3,482 Norwegian respondents. High scores on extraversion and openness to experiences increased the expected frequency of wine consumption, high score on agreeableness reduced the frequency of wine consumption, while scores on conscientiousness and neuroticism had no effects. For beer, there were no significant effects between personality traits and the frequency of consumption.
Forfattere
Annette BärSammendrag
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Sammendrag
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Forfattere
Bjørg Helen Nøstvold Ingrid Kvalvik Morten Heide Florent Govaerts Kristin Beate Hansen Sigridur Dalmannsdottir Hilde Halland Åse Vøllestad Susanne RamstadSammendrag
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Forfattere
Finn-Arne HaugenSammendrag
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Forfattere
Finn-Arne HaugenSammendrag
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Forfattere
Finn-Arne HaugenSammendrag
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Forfattere
Anna Birgitte MilfordSammendrag
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Sammendrag
Aim: Many countries lack informative, high‐resolution, wall‐to‐wall vegetation or land cover maps. Such maps are useful for land use and nature management, and for input to regional climate and hydrological models. Land cover maps based on remote sensing data typically lack the required ecological information, whereas traditional field‐based mapping is too expensive to be carried out over large areas. In this study, we therefore explore the extent to which distribution modelling (DM) methods are useful for predicting the current distribution of vegetation types (VT) on a national scale. Location: Mainland Norway, covering ca. 324,000 km2. Methods: We used presence/absence data for 31 different VTs, mapped wall‐to‐wall in an area frame survey with 1081 rectangular plots of 0.9 km2. Distribution models for each VT were obtained by logistic generalised linear modelling, using stepwise forward selection with an F‐ratio test. A total of 116 explanatory variables, recorded in 100 m × 100 m grid cells, were used. The 31 models were evaluated by applying the AUC criterion to an independent evaluation dataset. Results: Twenty‐one of the 31 models had AUC values higher than 0.8. The highest AUC value (0.989) was obtained for Poor/rich broadleaf deciduous forest, whereas the lowest AUC (0.671) was obtained for Lichen and heather spruce forest. Overall, we found that rare VTs are predicted better than common ones, and coastal VTs are predicted better than inland ones. Conclusions: Our study establishes DM as a viable tool for spatial prediction of aggregated species‐based entities such as VTs on a regional scale and at a fine (100 m) spatial resolution, provided relevant predictor variables are available. We discuss the potential uses of distribution models in utilizing large‐scale international vegetation surveys. We also argue that predictions from such models may improve parameterisation of vegetation distribution in earth system models.