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.
2015
Abstract
Remotely sensed data from airborne laser scanning (ALS) and interferometric synthetic aperture radar (InSAR) can greatly improve the precision of estimates of forest resource parameters such as mean biomass and biomass change per unit area. Field plots are typically used to construct models that relate the variable of interest to explanatory variables derived from the remotely sensed data. The models may then be used in combination with the field plots to provide estimates for a geographical area of interest with corresponding estimates of precision using model-assisted estimators. Previous studies have shown that field plot sizes found suitable for pure field surveys may be sub-optimal for use in combination with remotely sensed data. Plot boundary effects, co-registration problems, and misalignment problems favor larger plots because the relative impact of these effects on the models of relationships may decline by increasing plot size. In a case study in a small boreal forest area in southeastern Norway (852.6 ha) a probability sample of 145 field plots was measured twice over an 11 year period (1998/1999 and 2010). For each plot, field measurements were recorded for two plot sizes (200 m2 and 300/400 m2). Corresponding multitemporal ALS (1999 and 2010) and InSAR data (2000 and 2011) were also available. Biomass for each of the two measurement dates as well as biomass change were modeled for all plot sizes separately using explanatory variables from the ALS and InSAR data, respectively. Biomass change was estimated using model-assisted estimators. Separate estimates were obtained for different methods for estimation of change, like the indirect method (difference between predictions of biomass for each of the two measurement dates) and the direct method (direct prediction of change). Relative efficiency (RE) was calculated by dividing the variance obtained for a pure field-based change estimate by the variance of a corresponding estimate using the model-assisted approach. For ALS, the RE values ranged between 7.5 and 15.0, indicating that approximately 7.5–15.0 as many field plots would be required for a pure field-based estimate to provide the same precision as an ALS-assisted estimate. For InSAR, RE ranged between 1.8 and 2.5. The direct estimation method showed greater REs than the indirect method for both remote sensing technologies. There was clearly a trend of improved RE of the model-assisted estimates by increasing plot size. For ALS and the direct estimation method RE increased from 9.8 for 200 m2 plots to 15.0 for 400 m2 plots. Similar trends of increasing RE with plot size were observed for InSAR. ALS showed on average 3.2–6.0 times greater RE values than InSAR. Because remote sensing can contribute to improved precision of estimates, sample plot size is a prominent design issue in future sample surveys which should be considered with due attention to the great benefits that can be achieved when using remote sensing if the plot size reflects the specific challenges arising from use of remote sensing in the estimation. That is especially the case in the tropics where field resources may be scarce and inaccessibility and poor infrastructure hamper field work.
Abstract
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Authors
Zhibo Hamborg Gry Skjeseth Abdelhameed Elameen Sissel Haugslien Astrid Sivertsen Jihong Liu Clarke Qiao-Chun Wang Dag-Ragnar BlystadAbstract
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Authors
Bente FøreidAbstract
Soil cores from a field growing barley and barley mutants without root hairs under conventional and minimum tillage were sampled. They were X-ray scanned to produce a 3D image and then the roots were washed out and weight and length were determined by conventional means. Root volume and surface area were then calculated from the 3D images using state of the art software and methodology, and the measured and calculated measures were correlated. The only strong and significant correlation was between measured weight and calculated volume for mutants without root hairs. It is concluded that the software cannot segment out very small roots, but segmentation accuracy also depends on root structure in some unknown way. Any study using X-ray computed tomography to quantify roots as they grow in situ should start with a calibration for the conditions in question.
Authors
Olav Albert Høibø Eric Hansen Erlend NybakkAbstract
As societies urbanize, a growing proportion of the global population and an increasing number of housing units will be needed in urban areas. High-rise buildings and environmentally friendly, renewable materials must play important roles in sustainable urban development. To achieve this, it is imperative that policy makers, planners, architects, and construction companies understand consumer preferences. We use data from urban dwellers in the Oslo region of Norway to develop an understanding of material preferences in relation to environmental attitudes and knowledge about wood. We emphasise wood compared with other building materials in various applications (structural, exterior, and interior) within urban apartment blocks. We use 503 responses from a web panel. Our findings show that Oslo area consumers tend to prefer materials other than wood in various applications in apartment blocks, especially structural applications. Still, some respondent prefer wood, including some applications in apartment blocks where wood is currently not commonly used. The best target for wood-based urban housing includes younger people who have strong environmental values. As environmental attitudes evolve in society and a greater proportion of consumers search out environmentally friendly product alternatives, the opportunities for wood to gain market share will most likely increase.
Abstract
Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Østfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input.
Abstract
The woodland strawberry (Fragaria vesca) has become the model plant for the economically important, but genetically complex, octoploid F. × ananassa. Crown rot caused by the oomycete Phytophthora cactorum is a major problem for the strawberry industry and the identification and incorporation of efficient resistance genes into superior cultivars are important for breeding. In the present study, two experimental populations were used in inoculation experiments under controlled greenhouse condition. Studies of a sparse diallel cross between resistant and susceptible F. vesca genotypes concluded that resistance to crown rot is inherited as a dominant trait under nuclear control. Subsequently, an F2 population derived from the grandparents Bukammen (resistant) and Haugastøl 3 (susceptible) collected in Norway, were phenotyped in infection experiments and genotyped using genotyping-by-sequencing. A 416.2-cM linkage map was constructed, and a single major gene locus was identified on linkage group 6 that we attributed to resistance to Phytopthora infection. We propose to name the resistance locus RPc-1 (Resistance to Phytophthora cactorum 1). Gene prediction of the 3.3 Mb QTL recovered 801 genes of which 69 had a potential role in plant disease resistance.
Authors
Jonas Oliva S. Rommel Carl Gunnar Fossdal Ari Hietala M. Nemesio-Gorriz Halvor Solheim Malin ElfstrandAbstract
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Abstract
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Authors
Catherine A. Baroffio Anna K. Borg-Karlsson Michelle Fountain David Hall Baiba Ralle Pauline Richoz Aude Rogivue Lene Sigsgaard Nina Trandem Atle WibeAbstract
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