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.
2020
Authors
Tore SkrøppaAbstract
No abstract has been registered
Abstract
Controlled crosses were made on clones in a seed orchard and the pollination bags were kept on the branches until the cones were harvested. Cones after open pollination were collected at the same time. Seedlings from the controlled pollinations, from open pollination of the same maternal parent and from commercial provenances were grown in growth chambers and terminal bud set was recorded after short day treatments. The seedlings from the seeds of cones that were kept in the pollination bags had a significantly later bud set then expected based on comparisons with their half-sibs from open pollination. The difference corresponds to a decrease in altitude of 100 m at provenance level. It can be caused by epigenetic effects due to temperature differences inside and outside the bags during seed maturation.
Abstract
Skog er viktig i Norge. Det er uttalt politisk vilje til å styrke skogens bidrag for økonomisk verdiskaping i landbruket og for å nå viktige mål knyttet til energi, klima, miljøverdier og økosystemtjenester. Skogressursene er viktige for å opprettholde et bærekraftig landbruk og matproduksjon over hele landet, ettersom inntekt fra skogen bidrar til den totale inntekten for mange aktive bønder. Skogene er også viktige for rekreasjon og for folkehelsa. Skogtregenetiske ressurser i Norge brukes i produksjonsskogbruk, til skogplanting etter hogst og på annet areal, eller til treslagsskifte. De brukes også til juletreproduksjon, til landskapsformål eller i parker og hager....
Abstract
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Authors
Keni Ren Johannes Karlsson Markus Liuska Markku Hartikainen Inger Hansen Grete H. M. JørgensenAbstract
The growing interest in precision livestock farming is prompted by a desire to understand the basic behavioural needs of the animals and optimize the contribution of each animal. The aim of this study was to develop a system that automatically generated individual animal behaviour and localization data in sheep. A sensor-fusion-system tracking individual sheep position and detecting sheep standing/lying behaviour was proposed. The mean error and standard deviation of sheep position performed by the ultra-wideband location system was 0.357 ± 0.254 m, and the sensitivity of the sheep standing and lying detection performed by infrared radiation cameras and three-dimenional computer vision technology were 98.16% and 100%, respectively. The proposed system was able to generate individual animal activity reports and the real-time detection was achieved. The system can increase the convenience for animal behaviour studies and monitoring of animal welfare in the production environment.
Authors
Auvikki de Boon Camilla Sandström Ugo Arbieu Inger Hansen Lisa Lehnen Agnese Marino Mari Pohja-Mykrä Camilla Risvoll Geir-Harald Strand Katrina RønningenAbstract
Policy mixes (i.e. the total structure of policy processes, strategies, and instruments) are complex constructs that can quickly become incoherent, inconsistent, and incomprehensive. This is amplified when the policy mix strives to meet multiple objectives simultaneously, such as in the case of large carnivore policy mixes. Building on Rogge and Reichardt's analytical framework for the analysis of policy mixes, we compare the policy mixes of Norway, Sweden, Finland, the Netherlands, Germany (specifically Saxony and Bavaria), and Spain (specifically Castilla y León). The study shows that the large carnivore policy mixes in the case countries show signs of lacking vertical and horizontal coherence in the design of policy processes, weak consistency between objectives and designated policy instruments, and, as a consequence, lacking comprehensiveness. We conclude that creating consistent, coherent, and comprehensive policy mixes that build on multiple objectives requires stepping away from sectorized policy development, toward a holistic, systemic approach, strong collaborative structures across policy boundaries and regions, the inclusion of diverse stakeholders, and constant care and attention to address all objectives simultaneously rather than in isolation.
Abstract
Soil respiration is an important ecosystem process that releases carbon dioxide into the atmosphere. While soil respiration can be measured continuously at high temporal resolutions, gaps in the dataset are inevitable, leading to uncertainties in carbon budget estimations. Therefore, robust methods used to fill the gaps are needed. The process-based non-linear least squares (NLS) regression is the most widely used gap-filling method, which utilizes the established relationship between the soil respiration and temperature. In addition to NLS, we also implemented three other methods based on: 1) artificial neural networks (ANN), driven by temperature and moisture measurements, 2) singular spectrum analysis (SSA), relying only on the time series itself, and 3) the expectation-maximization (EM) approach, referencing to parallel flux measurements in the spatial vicinity. Six soil respiration datasets (2017–2019) from two boreal forests were used for benchmarking. Artificial gaps were randomly introduced into the datasets and then filled using the four methods. The time-series-based methods, SSA and EM, showed higher accuracies than NLS and ANN in small gaps (<1 day). In larger gaps (15 days), the performance was similar among NLS, SSA and EM; however, ANN showed large errors in gaps that coincided with precipitation events. Compared to the observations, gap-filled data by SSA showed similar degree of variances and those filled by EM were associated with similar first-order autocorrelation coefficients. In contrast, data filled by both NLS and ANN exhibited lower variance and higher autocorrelation than the observations. For estimations of the annual soil respiration budget, NLS, SSA and EM resulted in errors between −3.7% and 5.8% given the budgets ranged from 463 to 1152 g C m−2 year−1, while ANN exhibited larger errors from −11.3 to 16.0%. Our study highlights the two time-series-based methods which showed great potential in gap-filling carbon flux data, especially when environmental variables are unavailable.
Abstract
No abstract has been registered