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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.

2021

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Sammendrag

A call to governments to enact a strategy for a sustainable food system is high on the global agenda. A sustainable food system presupposes a need to go beyond a view of the food system as linear and narrow, to comprehend the food system as dynamic and interlinked, which involves understanding social, economic and ecological outcomes and feedbacks of the system. As such, it should be accompanied by strategic, collaborative, transparent, inclusive, and reflexive agenda-setting process. The concepts of, directionality relating to an agreed vision for a future sustainable food system, and, reflexivity which describes the capacity for critical deliberation and responsiveness, are particularly important. Based on those concepts, this paper proposes an evaluative framework to assess tools and instruments applied during the agenda-setting stage. We apply the evaluative framework to recent food policy processes in Finland and Sweden, revealing that their agenda-setting design cannot be assessed as fully addressing both directionality and reflexivity, thus possibly falling short of the policy design needed for enable more transformative policy approaches.

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Rapid deterioration of harvested macroalgal biomass is a challenge for macroalgal industry and can be overcome with the inexpensive ensiling preservation. To improve silage quality, Saccharina latissima and Alaria esculenta biomass was subjected to ensiling conditions following a 2 × 4 factorial design, with 2 prewilting treatments (no-prewilting and prewilted to 300 g DM kg−1 fresh biomass) and 4 additive treatments (no additive, formic acid, single and two species of Lactobacillus inoculant), and ensiled for 3 or 12 months at 15 °C. Acetate was the main fermentation product in these seaweed silages. Prewilting reduced the acetate, mannitol, and NH3 content in silages. In S. latissima silages without additives, prewilting led to less acidification (pH = 5.7). Also, prewilting caused protein and phlorotannin degradation. When treated with formic acid, the silage pH was below 4 regardless of the biomass’s moisture content. The use of Lactobacillus spp. inoculants was essential for lactate production in seaweed silages, and it significantly lowered silage pH in S. latissima and prewilted A. esculenta compared to silages with no additives. A high level of the phlorotannin content was preserved (> 90%) in the 3-month A. esculenta silages without prewilting. However, major reduction of antioxidant activity was observed in 12-month silages in both seaweed species. In conclusion, ensiling is a viable method for preserving Alaria and Saccharina biomass. Prewilting restricted silage fermentation, and both formic acid and bacterial additives facilitated silage acidification. However, there was no clear benefit of these treatments in preserving the antioxidant activity.

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Policy measures and management decisions aimed at enhancing the role of forests in mitigating climate change require reliable estimates of carbon (C)-stock dynamics in greenhouse gas inventories (GHGIs). The aim of this study was to assemble design-based estimators to provide estimates relevant for GHGIs using National Forest Inventory (NFI) data. We improve basic expansion (BE) estimators of living-biomass C-stock loss using only field data, by leveraging with remote sensing auxiliary data in model-assisted (MA) estimators. Our case studies from Norway, Sweden, Denmark, and Latvia covered an area of >70 Mha. Landsat-based forest cover loss (FCL) and one-time wall-to-wall airborne laser scanning (ALS) served as auxiliary data. ALS provided information on the C stock before a potential disturbance indicated by FCL. The use of FCL in MA estimators resulted in considerable efficiency gains, which in most cases were further increased by adding ALS. A doubling of efficiency was possible for national estimates and even larger efficiencies were observed at the subnational level. Average annual estimates were considerably more precise than pooled estimates of the NFI data from all years at once. The combination of remotely sensed and NFI field data yields reliable estimators, which is not necessarily the case when using remotely sensed data without reference observations.

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Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterized strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVMs) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products and less often by other vegetation products or by in situ field observations. In this study, we evaluate the performance of three methods for spatial representation of present-day vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DMs), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV; Community Land Model 4.5 Bio-Geo-Chemical cycles and Dynamical Vegetation). While DGVMs predict PFT profiles based on physiological and ecological processes, a DM relies on statistical correlations between a set of predictors and the modelled target, and the RS dataset is based on classification of spectral reflectance patterns of satellite images. PFT profiles obtained from an independently collected field-based vegetation dataset from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVMs often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, three new environmental variables (e.g. minimum temperature in May, snow water equivalent in October and precipitation seasonality) were selected as the threshold for the establishment of these high-latitude PFTs. We performed a series of sensitivity experiments to investigate if these thresholds improve the performance of the DGVM method. Based on our results, we suggest implementation of one of these novel PFT-specific thresholds (i.e. precipitation seasonality) in the DGVM method. The results highlight the potential of using PFT-specific thresholds obtained by DM in development of DGVMs in broader regions. Also, we emphasize the potential of establishing DMs as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

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Dollar spot, caused by at least five Clarireedia species (formerly Sclerotinia homoeocarpa F. T. Benn.), is one of the economically most important turfgrass diseases worldwide. The disease was detected for the first time in Scandinavia in 2013. There is no available information from Scandinavian variety trials on resistance to dollar spot in turfgrass species and cultivars (http://www.scanturf.org/). Our in vitro screening (in glass vials) of nine turfgrass species comprising a total of 20 cultivars showed that on average for ten Clarireedia isolates of different origin, the ranking for dollar spot resistance in turfgrass species commonly found on Scandinavian golf courses was as follows: perennial ryegrass = slender creeping red fescue > strong creeping red fescue > Kentucky bluegrass = velvet bentgrass > colonial bentgrass = Chewings fescue ≥ creeping bentgrass = annual bluegrass. Significant differences in aggressiveness among Clarireedia isolates of different origin were found in all turfgrass species except annual bluegrass (cv. Two Putt). The U.S. C. jacksonii isolate MB-01 and Canadian isolate SH44 were more aggressive than C. jacksonii isolates from Denmark and Sweden (14.10.DK, 14.15.SE, and 14.16.SE) in velvet bentgrass and creeping bentgrass. The Swedish isolate 14.112.SE was generally more aggressive than 14.12.NO despite the fact that they most likely belong to the same Clarireedia sp. The U.S. C. monteithiana isolate RB-19 had similar aggressiveness as the Scandinavian C. jacksonii isolates, but was less aggressive than two U.S. C. jacksonii isolates MB-01 and SH44. Thus, aggressiveness of Clarireedia isolates was more impacted by their geographic origin and less by species of the isolate and/or the host turfgrass species.

Sammendrag

The Norwegian Genetic Resource Centre estimated the inbreeding rate and thereby the effective population size for all of Norway’s cattle breeds at risk, using the method by Gutierrez et al 2008. When the conservation efforts began in 1990, these breeds were very small in number. However, the current population status shows that the breeds have been wisely managed.