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.
2011
Forfattere
Jutta KapferSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
I 2008 vart det for første gong her i landet funne mjøldogg på bjørkebladspirea. Også japanspirea er utsett for mjøldogg.
Forfattere
Trond RafossSammendrag
ClimaRice II is exploring the potential for use of mobile technologies in the context of climate change adaptation in agriculture. Modern mobile telephone technology is a key component of the ongoing communication revolution which in turn has great potentials for social change and development. The Indian telecommunication industry is the world's fastest growing industry with 811.59 million mobile phone subscribers as of March 2011. Most farmers are already using mobile phones for various day to day needs, but the technology has a wider potential in supporting their main profession; agriculture. Linking mobile technology with adaptation measures developed in ClimaRice projects could form new and powerful measures to meet the threats from climate change and provide support in sustaining rice production.
Forfattere
Kiran Jella Jella KiranSammendrag
ClimaRice is a research project on climate change adaptation and rice production, livelihoods and food security in Tamil Nadu and Andhra Pradesh, India (http://www.bioforsk.no/climarice/). One objective of ClimaRice is to explore the potential for use of mobile technologies in the context of climate change adaptation in agriculture. Modern mobile telephone technology is a key component of the ongoing communication revolution which in turn has great potentials for social change and development. Farmers deal with day to day variability in weather conditions. This adaptation of farmers, e.g. towards weather forecasts, could be viewed as a short term analogy to the long term adaptations to climate change. Improved access to weather forecasts and other relevant warnings of weather driven events relevant to rice cropping such as plant pest and disease forecasting is another priority of ClimaRice. Most farmers are already using mobile phones for various day to day needs, but the technology has a wider potential in supporting their main profession; agriculture. Linking mobile technology with adaptation measures developed in ClimaRice projects could form new and powerful measures to meet the threats from climate change and provide support in sustaining rice production. As a first step ClimaRice researchers are using mobile technology to collect field research data when taking observations and conducting survey interviews in the field. The major advantages of a work flow based on mobile field data collection is that the sampled data can be directly posted from the field and stored in an online central database, reducing the risk of data loss. The integrated support for determining geographical position (GPS) automates the procedure of associating such information with the observations taken. The location information can also be used for quality control, e.g. to check whether the observations are taken in accordance with a predefined sampling plan. In addition to improving quality and efficiency of field data collection, valuable experience about performance of mobile phones under tropical field conditions is expected. Important aspects that will be considered are battery capacity under operational data collection, network coverage, screen visibility etc.
Forfattere
Erik Næsset Terje Gobakken Svein Solberg Timothy Gregoire Ross Nelson Göran Ståhl Dan Johan WeydahlSammendrag
There is a need for accurate inventory methods that produce relevant and timely information on the forest resources and carbon stocks for forest management planning and for implementation of national strategies under the United Nations Collaborative Program on Reduced Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). Such methods should produce information that is consistent across various geographical scales. Airborne scanning Light Detection and Ranging (LiDAR) is among the most promising remote sensing technologies for estimation of forest resource information such as timber volume and biomass, while acquisition of three dimensional data with Interferometric Synthetic Aperture Radar (InSAR) from space is seen as a relevant option for inventory in the tropics because of its ability to “see through the clouds” and its potential for frequent updates at low costs. Based on a stratified probability sample of 201 field survey plots collected in a 960 km2 boreal forest area in Norway, we demonstrate how total above-ground biomass (AGB) can be estimated at three distinct geographical levels in such a way that the estimates at a smaller level always sum up to the estimate at a larger level. The three levels are (1) a district (the entire study area), (2) a village, local community or estate level, and (3) a stand or patch level. The LiDAR and InSAR data were treated as auxiliary information in the estimation. At the two largest geographical levels model-assisted estimators were employed. A model-based estimation was conducted at the smallest level. Estimates of AGB and corresponding error estimates based on (1) the field sample survey were compared with estimates obtained by using (2) LiDAR and (3) InSAR data as auxiliary information. For the entire study area, the estimates of AGB were 116.0, 101.2, and 111.3 Mg ha−1, respectively. Corresponding standard error estimates were 3.7, 1.6, and 3.2 Mg ha−1. At the smallest geographical level (stand) an independent validation on 35 large field plots was carried out. RMSE values of 17.1–17.3 Mg ha−1 and 42.6–53.2 Mg ha−1 were found for LiDAR and InSAR, respectively. A time lag of six years between acquisition of InSAR data and field inventory has introduced some errors. Significant differences between estimates and reference values were found, illustrating the risk of using pure model-based methods in the estimation when there is a lack of fit in the models. We conclude that the examined remote sensing techniques can provide biomass estimates with smaller estimated errors than a field-based sample survey. The improvement can be highly significant, especially for LiDAR.
Sammendrag
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Forfattere
Helge Bonesmo Odd Magne Harstad Arne Oddvar Skjelvåg Arnold Arnoldussen Ole Einar Tveito Ove Klakegg Harald Volden Egil Prestløkken Tonje Storlien Kjell Staven Otto SjelmoSammendrag
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Forfattere
Helge Bonesmo Odd Magne Harstad Arne Oddvar Skjelvåg Arnold Arnoldussen Ole Einar Tveito Ove Klakegg Harald Volden Egil Prestløkken Tonje Storlien Kjell Staven Otto SjelmoSammendrag
Det er ikke registrert sammendrag