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.
2016
Forfattere
Sebastian EiterSammendrag
Forskere i det europeiske COST-nettverket «Urban Agriculture Europe» har utviklet et felles begrepsapparat som grunnlag for politikkutforming. Urbant landbruk er definert i henhold til seks dimensjoner, og delt inn i de to hovedtypene urban gårdsdrift som næring, og urban hagedyrking med liten eller ingen økonomisk betydning. Mangfoldet som 14 undertyper av urbant landbruk representerer, gjør det til en arena for mange politikkfelt. For å kunne nytte det urbane landbrukets potensiale for økonomiske, sosiale, miljø- og helsemessige gevinster fullt ut, bør politikkfeltene fordele hovedansvaret for ulike typer urbant landbruk seg imellom.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Göran Ståhl Svetlana Saarela Sebastian Schnell Sören Holm Johannes Breidenbach Sean P. Healey Paul L. Patterson Steen Magnussen Erik Næsset Ronald E. McRoberts Timothy G. GregoireSammendrag
This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes design-based and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data..We review studies on large-area forest surveys based on model-assisted, model-based, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters.
Forfattere
Ari HietalaSammendrag
Det er ikke registrert sammendrag
Sammendrag
Food production contributes considerably to global greenhouse gas (GHG) emissions. Animal products – particularly meat from ruminants – generally have higher GHG emissions than plant products. Over the last few decades the global per capita consumption of animal products has increased. This has a negative impact on climate change, land and water availability, and human health. We are faced with the two-fold challenge of reducing GHG emissions while still producing enough food for our growing population. Part of the solution could be for consumers to change towards a more sustainable diet. In this paper we take Norway as a case study for estimating optimal taxes and subsidies on different food items which can change consumption patterns in order to reduce the GHG emissions derived from the average Norwegian diet. In the estimate we ensure that the average calorie intake with the new diet remains the same as with the current diet, and factor in other health considerations. Our findings suggest that limited but useful emission reduction targets can be set with only a few changes in diets. The methodology presented in this paper may be used to estimate optimal climate taxes and subsidies under different emission, quantities, taxes, subsidies, and health constraints.
Forfattere
Bruce Talbot Marek Marian Pierzchala Jan Bjerketvedt Dag FjeldSammendrag
Det er ikke registrert sammendrag
Sammendrag
The success of precision agriculture relies largely on our ability to identify how the plants’ growth limiting factors vary in time and space. In the field, several stress factors may occur simultaneously, and it is thus crucial to be able to identify the key limitation, in order to decide upon the correct contra-action, e.g., herbicide application. We performed a pot experiment, in which spring wheat was exposed to water shortage, nitrogen deficiency, weed competition (Sinapis alba L.) and fungal infection (Blumeria graminis f. sp. tritici) in a complete, factorial design. A range of sensor measurements were taken every third day from the two-leaf stage until booting of the wheat (BBCH 12 to 40). Already during the first 10 days after stress induction (DAS), both fluorescence measurements and spectral vegetation indices were able to differentiate between non-stressed and stressed wheat plants exposed to water shortage, weed competition or fungal infection. This meant that water shortage and fungal infection could be detected prior to visible symptoms. Nitrogen shortage was detected on the 11–20 DAS. Differentiation of more than one stress factors with the same index was difficult.
Forfattere
Bolette BeleSammendrag
Det er ikke registrert sammendrag
Forfattere
Yngve RekdalSammendrag
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Sammendrag
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