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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.

2025

Abstract

Sammendrag på norsk I Norge beiter kjøttfe i store områder av boreal produksjonsskog preget av flatehogst på sommeren (mai-september). Vi studerte først mat- og habitatvalg av disse kyrne (Artikkel I– II), og deretter effektene av storfe på flora og fauna (Artikkel III-V). Datainnsamlingen foregikk i Sørost-Norge i 2015-2017 (Furnes/Vang og Stange/Romedal) og 2021-2023 (Steinvik og Deset). Vi studerte kyrnes ressursvalg ved å klassifisere deres adferd ved hjelp av GPS og akselerasjonsdata, ved å hente inn (fra kart) og måle (i felt) habitatvariabler, ved å samle inn møkkprøver til mikrohistologiske analyser og ved å modellere ressursseleksjonsfunksjoner. Vi fokuserte på unge granplantefelt for å studere effektene av kjøttfe på flora og fauna, siden kyrene selekterer for denne skogstypen. Dessuten har små grantrær høy økonomisk verdi og unge granplantefelt er rikere i blomster og pollinatorer enn det resterende skoglandskapet. På 24 unge granplantefelt satt vi opp parede prøveflater (20x20 m hver), hvorav en omgitt av et gjerde. Vi så på unge trær, vegetasjonen i feltsjiktet og blomsterbesøkende insekter. Siden halvparten av disse granplantefeltene lå innenfor, og den andre halvparten utenfor beiteområdene, kunne vi skille effektene av storfe fra effektene av hjortedyr, som lever vilt i disse skogene. Interaksjoner mellom storfe og hjortedyr studerte vi ved å sette opp viltkamera på de samme granplantefelt og ved å gjennomføre møkktellinger langs et rutemønster i ett av beiteområdene. Kyrne hadde en gressrik diett og selekterte for gressrike habitater, både på stor og på liten skala (Artikkel I). Storfe selekterte for forskjellige habitatvariabler (liten skala) avhengig av adferden: Når de beitet, selekterte de for gressrikt habitat, og når de hvilte, selekterte de for gressrikt habitat med lite helling og høy kronedekning (Artikkel II). Storfe førte til bittelitt høyere dødelighet av unge grantrær, men ikke til høyere risiko for tråkk- og beiteskader (Artikkel III). Storfe fjernet vegetasjon som konkurrerte med unge grantrær, det vil si unge løvtrær og vegetasjon i feltsjiktet (Artikkel III). Storfe påvirket plante-pollinatorsamfunnet på en annen måte enn hjortevilt: Utgjerding av klovdyr utenfor beiteområde (hjortedyr) førte til lavere abundans av blomster, mens utgjerding av klovdyr innenfor beiteområde (hjortedyr og storfe) førte til lavere abundans av blomster og lavere abundans av blomsterbesøkende insekter (Artikkel IV). Elg brukte andre habitattyper enn storfe (Artikkel V). Elgen sitt bruk av unge granplantefelt avtok med økende bruk av storfe (Artikkel V). Mulige beiteinnskrenkende tiltak, samt bevaring av artsmangfoldet i boreal produksjonsskog ble drøftet, og anbefalinger for videre forskning ble gitt.

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Abstract

Environmental research is facing a drastic increase of available high-quality data, not the least due to the eLTER activities. Here simultaneous time series of numerous observables from the atmosphere, soil, streams, lakes and groundwater, etc., and comprising both abiotic and biotic variables will be made available from hundreds of sites. On the one hand quality control of these large data sets becomes a major challenge. On the other hand, though, it opens up completely new options for science as long as some key problems are solved:· How to differentiate between different effects?· How to deal with the filter effects of environmental systems?· How to identify unexpected relationships that a model would not depict?However, environmental sciences still lack a toolbox of approved integrated exploratory data analysis approaches to tackle these challenges in a systematic way. Here we suggest a combination of different methods that proved very efficient both in terms of data quality control and of exploratory data analysis for large sets of time series. Examples will be presented from the AgroScapeLab Quillow (LTER site DE-07-UM, Germany) and the Hurdal ICOS and ICP Forest Level II site (Norway). The Hurdal site is planned to be established as an elTER site as well.Any change of boundary conditions, of input fluxes, emerging invasive species etc. (termed “signal propagation” for short) in environmental systems is subject to filtering effects. A key feature thereof is low-pass filtering. Here we suggest the new Cumulative Periodogram Convexity (CPC) index to quantify the effect size for comparison of various time series. Principal Component Analysis of time series (termed Empirical Orthogonal Function approach in climatology) is suggested as another decisive step. Loadings on single components can be used for assessing the size of single effects on observed time series. Visualization of the communalities and of similarities between different observables and sites in a combination of Self-Organizing Maps and Sammon Mapping allows a rapid survey of some tens to hundreds of time series at a glance, e.g., for quality control. Additional consideration of the CPC index proved a powerful tool for identification of the respective key drivers and of the pathways of signal propagation through environmental systems, comprising both biotic and abiotic observables. Applying machine learning approaches to principal components rather than to the raw data facilitates developing a better understanding of complex interactions in environmental systems. To conclude, we see great potential in a systematic combination of existing approaches deserving to be explored further.

Abstract

Drought stress disrupts plant growth, metabolism, and reproduction, with devastating effects on crop productivity worldwide. Blackcurrant, although rich in health-promoting compounds, is highly vulnerable to water deficits, often producing fewer flowers and aborting developing fruit. Previous transcriptome studies provided only fragmented insights, and no reference genome existed for the Grossulariaceae family until now. Without such genomic tools, identifying precise stress-responsive genes and linking them to metabolite dynamics remained challenging. Based on these challenges, there is a pressing need to conduct integrated genome-scale, transcriptomic, and metabolomic studies to uncover blackcurrant’s drought response mechanisms.

Abstract

Sweet cherries are grown in areas with suitable local climatic conditions up to 60°N in Norway. All orchards have high density planting systems and are rain covered from the bloom to the end of the harvest. All orchards are fertigated and the production is aimed to supply the domestic market with high quality fruit from early July and to the end of August. At NIBIO Ullensvang a large number of sweet cherry cultivars and advanced selections from worldwide breeding programs have been evaluated continuously since 1959. However, despite of relatively extensive list of recommended cultivars, cv. 'Lapins' has become dominant with 60% of the total sweet cherry volume in Norway, and causes high pressure in the market when too much fruit are delivered at the same time. The most effective way to extend the cherry market season is an introduction and cultivation of new early or late ripening sweet cherry cultivars. During the last years, approximately fifty cultivars and advanced selections have been evaluated. Along with earlier recommended cultivars ‘Folfer’, ‘Van’, ‘Lapins’, ‘Regina’ and ‘Sweetheart’, the following cultivars can be recommended for extended testing commercially: a) for early season: ‘Adelka’ (for local market), ‘Sweet Aryana’ and ‘Bellise’ (primary for local market), b) for mid-season: ‘Edit’, ‘Brooks’ (limited testing) and ‘Grace Star’, c) for late season: ’SPC 342’, ‘LaLa Star’, ‘Royal Edie’, ‘Tamara’ and ‘Royal Helen’.

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Abstract

Litter decomposition is coupled to carbon (C) sequestration through C release to the atmosphere, C transformation and nutrient release to the soil. We investigated if clear-cutting has long-term effects on this vital ecological process and consequently on C dynamics in boreal forests using twelve pairs of previously clear-cut and near-natural forests. Three litterbag experiments were conducted using (I) standardised spruce and bilberry litter, (II) melanised and non-melanised fungal necromass and (III) rooibos and green tea. We found weak and inconsistent effects of harvesting history, that did not depend on litter quality or mesofauna exclusion. Litter quality was more important in explaining net mass remaining for fungal necromass than for aboveground plant litter. Mesofauna exclusion had only marginal effects on initial litter decomposition. Results obtained with the highly standardised Tea Bag Index were not readily comparable to those of the plant litter or fungal necromass and we therefore question its use in this regional context. Further, we show that net mass or C remaining in the litterbags do not correlate consistently with in situ soil respiration. This finding is discussed in relation to previous measurements of soil C fluxes from the same system. In conclusion, we suggest that potential disturbances to the physical environment or the capacity of the decomposer community to facilitate litter decomposition are no longer clearly evident when clear-cut stands approach maturity.