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.
2022
Authors
Johanna Eva Bodin Nur Duale Anne-Marthe Ganes Jevnaker Monica Sanden Ville Erling Sipinen Tage Thorstensen Rose VikseAbstract
No abstract has been registered
Authors
Johanna Eva Bodin Nur Duale Anne-Marthe Ganes Jevnaker Monica Sanden Ville Erling Sipinen Tage Thorstensen Rose VikseAbstract
No abstract has been registered
Authors
Johanna Eva Bodin Nur Duale Anne-Marthe Ganes Jevnaker Monica Sanden Ville Erling Sipinen Tage Thorstensen Rose VikseAbstract
No abstract has been registered
Authors
Bjørnar Ytrehus Jan Ove Bustnes Bård-Jørgen Bårdsen Katrine Eldegard Kyrre Kausrud Brett Sandercock Paul Ragnar Berg Anders Bryn Sonya Rita Geange Erik Georg Bø-Granquist Kjetil Hindar Lars Robert Hole Johanna Järnegren Lawrence R. Kirkendall Anders Nielsen Erlend Birkeland Nilsen Gaute VelleAbstract
Background Spring hunting for ducks (Lodden in Northern Sami) is part of the Sami hunting and trapping culture. In Norway, this traditional hunting has been permitted in Kautokeino Municipality in accordance with the exception provision in the Wildlife Act Section 15, with quotas for males of several duck species. However, hunting in the spring may be in conflict with the Nature Diversity Act's principle for species management, saying (quote from Section 15): “Unnecessary harm and suffering caused to animals occurring in the wild and their nests, lairs and burrows shall be avoided. Likewise, unnecessary pursuing of wildlife shall be avoided.” Furthermore, in accordance with international legislation and agreements, the Wildlife Act (Section 9) states that the hunting season should not be set to the nesting and breeding season for the species in question. The Norwegian Environment Agency (NEA) asked VKM to (1) assess risk and risk-reducing measures on biodiversity and animal welfare when conducting spring hunting of ducks. The terms of reference were additionally clarified by the NEA to include assessments of the risks associated with hunting quotas of up to 150, 300, and 500 male individuals, on the populations of mallard (Anas platyrhynchos), tufted duck (Aythya fuligula), velvet scoter (Melanitta fusca), common scoter (Melanitta nigra), long-tailed duck (Clangula hyemalis), and red-breasted merganser (Mergus serrator). VKM was furthermore asked to (2) point out risk-reducing measures in scenarios with hunting bags corresponding to the mentioned quotas of all the six species. Method VKM appointed a project group to answer the request from NEA and assess the risks to biodiversity and animal welfare posed by spring hunting for adult male ducks. The project group narrowed down the scope of the biodiversity risk assessment to encompass risks for local populations of six target species: mallard, tufted duck, velvet scoter, common scoter, long-tailed duck, and red-breasted merganser, and non-target migratory waterbirds. Negative impacts on biodiversity was defined as negative effects on population viability. The VKM project group gathered data from publications retrieved from literature searches and reports from Kautokeino municipality to the Finnmark Estate (Finnmarkseiendommen), which were made available to the group by the Norwegian Environment Agency. Hunting statistics were acquired from Statistics Norway (Statistisk sentralbyrå; SSB). During the assessment, several critical knowledge gaps and uncertainties were identified. The main obstacle for assessment of the impact of spring hunting on viability of local populations in Kautokeino, is the lack of data on relevant population sizes and demographic rates for the six target species. The available population estimates are partly based on almost 30-year-old bird counts. In addition, knowledge about spatial and temporal distributions of each species, combined with local or remote-sensed data on ice breakup, is needed to estimate the proportion of the population being effectively hunted in early spring when ducks are congregating on available ice-free waters. Such knowledge, combined with information about where, when, how and by how many hunters the hunting is performed, is also critical for sound assessments of risk to biodiversity and harm to bird welfare. Improved data on hunting bags (reliable, spatially explicit, and detailed) and frequency of wounding and crippling is also needed to provide accurate assessments. The project group performed modelling of harvest scenarios for a range of conditions (e.g., number of birds harvested, reduced breeding success caused by indirect effects of disturbance, environmental stochasticity, and spatial variation in habitat) to assess how sensitive the populations are to different parameters and model assumptions. ..............................
Authors
Geir-Harald StrandAbstract
No abstract has been registered
Authors
Katrine Eldegard Daniel Flø Lawrence R. Kirkendall Martin Malmstrøm Anders Nielsen Claus Rasmussen Hugo de Boer Kjetil Hindar Johanna Järnegren Kyrre Kausrud Eli Knispel Rueness Eva Bonsak Thorstad Gaute VelleAbstract
No abstract has been registered
Authors
Kim Viggo Paulsen Weiby Sophie Julie Krizsan Margrete Eknæs Angela Dagmar Schwarm Anne Cathrine Whist Ingunn Schei Håvard Steinshamn Peter Lund Karen A. Beauchemin Ingjerd DønnemAbstract
Grass-clover silage constitutes a large part of ruminant diets in Northern and Western Europe, but the impact of silage quality on methane (CH4) production is largely unknown. This study was conducted to identify the quality attributes of grass silage associated with variation in CH4 yield. We expected that silage nutrient concentrations and silage fermentation products would affect CH4 yield, and that these factors could be used to predict the methanogenic potential of the silages. Round bales (n = 78) of grass and grass-clover silage from 37 farms in Norway were sampled, incubated, and screened for in vitro CH4 yield, i.e. CH4 production expressed on the basis of incubated organic matter (CH4-OM) and digestible OM (CH4-dOM) using sheep. Concentration of indigestible neutral detergent fiber (iNDF) was quantified using the in situ technique. The data were subjected to correlation and principal component analyses. Stepwise multiple regression was used to model methanogenic potential of silages. Among all investigated silage composition variables, neutral detergent fiber (aNDFom) and water-soluble carbohydrate (WSC) concentrations obtained the greatest correlations to CH4-OM (r = −0.63 and r = 0.57, respectively, P < 0.001), while concentration of iNDF negatively correlated with CH4-OM (r = −0.48, P < 0.001). In vivo organic matter digestibility (OMD) and concentration of ammonia-N (NH3-N) in silages were also correlated to CH4-OM (r = 0.44 and r = −0.32, P < 0.001 and P < 0.01, respectively). The stepwise regression using CH4-OM as response variable included aNDFom, WSC, iNDF, silage propionic acid and pH in descending order. The stepwise regression using CH4-dOM as response variable included WSC, aNDFom and iNDF in descending order. Among in vitro rumen short chain fatty acids (SCFA), molar proportion of butyrate was the most prominent in increasing CH4-OM and CH4-dOM (r = 0.23 and r = 0.36, P < 0.05 and P < 0.01, respectively), while molar proportion of propionate was the most prominent SCFA in reducing CH4-OM and CH4-dOM (r = −0.23 and r = −0.26, respectively, P < 0.05). Regression models that account for silage quality attributes can be used to predict CH4 yield from silages with a coefficient of determination (R2) between 0.33 (CH4-dOM) and 0.65 (CH4-OM). In conclusion, concentration of WSC increased in vitro CH4-OM and CH4-dOM, while concentration of aNDFom and iNDF decreased CH4-OM and CH4-dOM in grass silages.
Authors
P.H. Templer J.L. Harrison Francesca Pilotto A. Flores-Díaz P. Haase W.H. McDowell R. Sharif H. Shibata D. Blankman A. Avila U. Baatar H.R. Bogena I. Bourgeois J. Campbell T. Dirnböck W.K. Dodds Marit Hauken I. Kokorite K. Lajtha I.-L. Lai H. Laudon T.C. Lin S.R.M. Lins H. Meesenburg P. Pinho A. Robison M. Rogora B. Scheler P. Schleppi R. Sommaruga T. Staszewski M. TakaAbstract
Previous studies have evaluated how changes in atmospheric nitrogen (N) inputs and climate affect stream N concentrations and fluxes, but none have synthesized data from sites around the globe. We identified variables controlling stream inorganic N concentrations and fluxes, and how they have changed, by synthesizing 20 time series ranging from 5 to 51 years of data collected from forest and grassland dominated watersheds across Europe, North America, and East Asia and across four climate types (tropical, temperate, Mediterranean, and boreal) using the International Long-Term Ecological Research Network. We hypothesized that sites with greater atmospheric N deposition have greater stream N export rates, but that climate has taken a stronger role as atmospheric deposition declines in many regions of the globe. We found declining trends in bulk ammonium and nitrate deposition, especially in the longest time-series, with ammonium contributing relatively more to atmospheric N deposition over time. Among sites, there were statistically significant positive relationships between (1) annual rates of precipitation and stream ammonium and nitrate fluxes and (2) annual rates of atmospheric N inputs and stream nitrate concentrations and fluxes. There were no significant relationships between air temperature and stream N export. Our long-term data shows that although N deposition is declining over time, atmospheric N inputs and precipitation remain important predictors for inorganic N exported from forested and grassland watersheds. Overall, we also demonstrate that long-term monitoring provides understanding of ecosystems and biogeochemical cycling that would not be possible with short-term studies alone.
Abstract
The assessment of forest abiotic damages such as snow breakage is important to ensure compensation to forest owners. Currently, information on the extent of snow breakage is gathered through time-consuming and potentially biased field surveys. In such situations where field surveys are still common practice, unmanned aerial vehicles (UAVs) are increasingly being used to provide a more cost-efficient and objective methods to answer forest information needs. Further, the advent of sophisticated computer vision techniques such as convolutional neural networks (CNNs) offers new ways to analyze image data more efficiently and accurately. We proposed an object detection method to automatically identify trees and classify them according to the damage by snow based on a YOLO CNN architecture. UAV imagery collected across 89 study areas and over the course of the entire year were manually annotated into a total of >55 K single trees classified as healthy, damaged, or dead. The annotated trees, along with the corresponding UAV imagery were used to train a YOLOv5 object detection model. Furthermore, we tested the effect of seasonality, and varying atmospheric and lighting conditions on the model’s performance. Based on an independent test set of data we found that the general model including all of the data (i.e. any seasons, atmospheric conditions, and time of the day) outperformed all other tested scenarios (i.e. precision = 62 %; recall = 61 %). Furthermore, we found that despite the fact that the snow damaged trees represented a minority class (i.e. 16 % of the annotated trees), they were detected with the largest precision (76 %) and recall (78 %). Finally, the general model transferred well across the variation in seasons, atmospheric and illumination conditions, making it suitable for usage for any new UAV image acquisition.
Abstract
No abstract has been registered