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.
2013
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Alice Budai Samuel Abiven Morten Grønli Liang Wang Michael Jerry Antal Claudia Forte Daniel RasseSammendrag
Det er ikke registrert sammendrag
Forfattere
Erik J. JonerSammendrag
Det er ikke registrert sammendrag
Forfattere
Daniel RasseSammendrag
Det er ikke registrert sammendrag
Sammendrag
Artikkelen gjennomgår nyere norsk kart- og geodatahistorie (1970 - 2000) og analyserer bakteppet for etableringen av den nasjonale geografiske infrastrukturen Norge digitalt
Forfattere
Tatsiana EspevigSammendrag
Det er ikke registrert sammendrag
Forfattere
Kathrin Seidel Johannes Kahl Flavio Paoletti Inés Birlouez-Aragone Nicolaas Busscher Ursula Kretzschmar Marjo Särkka-Tirkkonen Randi Seljåsen Fiorella Sinesio Torfinn Torp Irene BaiamonteSammendrag
Det er ikke registrert sammendrag
Forfattere
Randi Seljåsen Hanne L. Kristensen Charlotte Lauridsen Gabriela S Wyss Ursula Kretzschmar Inés Birlouez-Aragone Johannes KahlSammendrag
Det er ikke registrert sammendrag
Forfattere
Zahra Kalantari Steve W. Lyon Lennart Folkeson Helen French Jannes Stolte Per-Erik Jansson Mona SassnerSammendrag
A physically-based, distributed hydrological model (MIKE SHE) was used to quantify overland runoff in response to four extreme rain events and four types of simulated land use measure in a catchment in Norway. The current land use in the catchment comprises arable lands, forest, urban areas and a stream that passes under a motorway at the catchment outlet. This model simulation study demonstrates how the composition and configuration of land use measures affect discharge at the catchment outlet differently in response to storms of different sizes. For example, clear-cutting on 30% of the catchment area produced a 60% increase in peak discharge and a 10% increase in total runoff resulting from a 50-year storm event in summer, but the effects on peak discharge were less pronounced during smaller storms. Reforestation of 60% of the catchment area was the most effective measure in reducing peak flows for smaller (2-, 5- and 10-year) storms. Introducing grassed waterways reduced water velocity in the stream and resulted in a 28% reduction in peak flow at the catchment outlet for the 50-year storm event. Overall, the results indicate that the specific effect of land use measures on catchment discharge depends on their spatial distribution and on the size and timing of storm events.
Forfattere
Johannes Breidenbach Clara Antón Fernández Hans Petersson Ronald E. McRoberts Rasmus AstrupSammendrag
National Forest Inventories (NFIs) provide estimates of forest parameters for national and regional scales. Many key variables of interest, such as biomass and timber volume, cannot be measured directly in the field. Instead, models are used to predict those variables from measurements of other field variables. Therefore, the uncertainty or variability of NFI estimates results not only from selecting a sample of the population but also from uncertainties in the models used to predict the variables of interest. The aim of this study was to quantify the model-related variability of Norway spruce (Picea abies [L.] Karst) biomass stock and change estimates for the Norwegian NFI. The model-related variability of the estimates stems from uncertainty in parameter estimates of biomass models as well as residual variability and was quantified using a Monte Carlo simulation technique. Uncertainties in model parameter estimates, which are often not available for published biomass models, had considerable influence on the model-related variability of biomass stock and change estimates. The assumption that the residual variability is larger than documented for the models and the correlation of within-plot model residuals influenced the model-related variability of biomass stock change estimates much more than estimates of the biomass stock. The larger influence on the stock change resulted from the large influence of harvests on the stock change, although harvests were observed rarely on the NFI sample plots in the 5-year period that was considered. In addition, the temporal correlation between model residuals due to changes in the allometry had considerable influence on the model-related variability of the biomass stock change estimate. The allometry may, however, be assumed to be rather stable over a 5-year period. Because the effects of model-related variability of the biomass stock and change estimates were much smaller than those of the sampling-related variability, efforts to increase the precision of estimates should focus on reducing the sampling variability. If the model-related variability is to be decreased, the focus should be on the tree fractions of living branches as well as stump and roots.