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
Abstract
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.
Abstract
No abstract has been registered
Authors
Seyda Özkan_Gülzari Grete H. M. Jørgensen Svein Eilertsen Inger Hansen Snorre Hagen Ida Marie Luna Fløystad Rupert PalmeAbstract
Several non-invasive methods for assessing stress responses have been developed and validated for many animal species. Due to species-specific differences in metabolism and excretion of stress hormones, methods should be validated for each species. The aim of this study was to conduct a physiological validation of an 11-oxoaetiocholanolone enzyme immunoassay (EIA) for measuring faecal cortisol metabolites (FCMs) in male reindeer by administration of adrenocorticotrophic hormone (ACTH; intramuscular, 0.25 mg per animal). A total of 317 samples were collected from eight male reindeer over a 44 h period at Tverrvatnet in Norway in mid-winter. In addition, 114 samples were collected from a group of reindeer during normal handling and calf marking at Stjernevatn in Norway. Following ACTH injection, FCM levels (median and range) were 568 (268–2415) ng/g after two hours, 2718 (414–8550) ng/g after seven hours and 918 (500–6931) ng/g after 24 h. Levels were significantly higher from seven hours onwards compared to earlier hours (p < 0.001). The FCM levels at Stjernevatn were significantly (p < 0.001) different before (samples collected zero to two hours; median: 479 ng/g) and after calf marking (eight to ten hours; median: 1469 ng/g). Identification of the faecal samples belonging to individual animals was conducted using DNA analysis across time. This study reports a successful validation of a non-invasive technique for measuring stress in reindeer, which can be applied in future studies in the fields of biology, ethology, ecology, animal conservation and welfare.
Authors
Junbin ZhaoAbstract
As the main drivers of climate change, greenhouse gas (e.g., CO2 and CH4) emissions have been monitored intensively across the globe. The static chamber is one of the most commonly used approaches for measuring greenhouse gas fluxes from ecosystems (e.g., stem/soil respiration, CH4 emission, etc.) because of its easy implementation, high accuracy and low cost (Pumpanen et al., 2004). To perform the measurements, a gas analyzer is usually used to measure the changes of greenhouse gas concentrations within a closed chamber that covers an area of interest (e.g., soil surface) over a certain period of time (usually several minutes). The flux rates (F) are then calculated from the recorded gas concentrations assuming that the changing rate is linear: F = vol/(R · T a · area) · dG/dt where vol is the volume of the chamber (l), R is the universal gas constant (l atm K-1 mol-1), Ta is the ambient temperature (K), area is the area of the chamber base (m2 ), and dG/dt is the rate of the measured gas concentration change over time t (ppm s-1) (i.e., the slope of the linear regression).
Authors
Mette Thomsen Eldrid Lein Molteberg Anne-Berit Wold Belachew Asalf Tadesse Pia Heltoft Thomsen Arne HermansenAbstract
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Authors
Merike Sõmera Anders Kvarnheden Cécile Desbiez Dag-Ragnar Blystad Pille Sooväli Jiban Kumar Kundu Mark Gantsovski Jim Nygren Hervé Lecoq Eric Verdin Carl Jonas Jorge Spetz Lucie Tamisier Erkki Truve Sebastien MassartAbstract
High-throughput sequencing technologies were used to identify plant viruses in cereal samples surveyed from 2012 to 2017. Fifteen genome sequences of a tenuivirus infecting wheat, oats, and spelt in Estonia, Norway, and Sweden were identified and characterized by their distances to other tenuivirus sequences. Like most tenuiviruses, the genome of this tenuivirus contains four genomic segments. The isolates found from different countries shared at least 92% nucleotide sequence identity at the genome level. The planthopper Javesella pellucida was identified as a vector of the virus. Laboratory transmission tests using this vector indicated that wheat, oats, barley, rye, and triticale, but none of the tested pasture grass species (Alopecurus pratensis, Dactylis glomerata, Festuca rubra, Lolium multiflorum, Phleum pratense, and Poa pratensis), are susceptible. Taking into account the vector and host range data, the tenuivirus we have found most probably represents European wheat striate mosaic virus first identified about 60 years ago. Interestingly, whereas we were not able to infect any of the tested cereal species mechanically, Nicotiana benthamiana was infected via mechanical inoculation in laboratory conditions, displaying symptoms of yellow spots and vein clearing evolving into necrosis, eventually leading to plant death. Surprisingly, one of the virus genome segments (RNA2) encoding both a putative host systemic movement enhancer protein and a putative vector transmission factor was not detected in N. benthamiana after several passages even though systemic infection was observed, raising fundamental questions about the role of this segment in the systemic spread in several hosts.
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No abstract has been registered