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.
2021
Sammendrag
Long-term machine-derived data sets comprising 140,000 trees were collected from four harvesters of equal age and similar working conditions, into two machine size classes, viz. two Ponsse Bears and two smaller Ponsse Beavers. Productivity functions for each size class were modelled using a nonlinear mixed effects approach. Based on these functions, unit costs and their sensitivity to utilization rates and cost of capital were assessed. Results showed that despite considerably higher capital costs (32%) on the Bear, a 50% higher mean productivity resulted in a unit cost only 17% higher than the Beaver in a disadvantageous scenario (high interest rates and low utilisation), and a 6% lower unit cost than the Beaver in an advantageous scenario (low interest and high utilisation), within the range of tree sizes observed. Between these extremes, only marginal differences in unit costs were observed. This demonstrates that the difference in ownership and operating costs between larger and smaller harvesters is largely negated by the difference in productivity rates. These results can provide useful insight into timber harvester investment decisions. Harvesters from two adjacent size classes can be used interchangeably at the same unit cost within a wide range of tree sizes despite productivity differences. It should be noted that increased repair costs and an eventual reduction in expected economic lifetime on a smaller harvester, or the negative effects of using a larger harvester in smaller trees, e.g. thinning operations, were not taken into account in this work.
Sammendrag
Norwegian plum production is characterized by climatic limitations, different flowering time, deficiently of wholly-adapted cultivars and appropriate pollen donors for cultivars that can be grown in this region. This study evaluated the progamic phase of fertilization and fruit set in four European plum cultivars (´Mallard´, ´Edda´, ´Jubileum´, and ´Reeves´) after crossing with different pollinizers over two years (2018/2019). Reproductive parameters, in vitro pollen germination, number of pollen tubes in the upper part of the style and locule of the ovary, number of pistils with ovule penetrated by pollen tube, fruit set in all crossing combinations, and fruit set in open pollination of pollen recipient cultivars showed different adaptability of both recipient and donor cultivars to the specific ecological conditions prevailing in Western Norway. The pollinizers ´Victoria´, ´Opal´ and ´Č. Lepotica´ proved to be a very good pollinizers for cultivar ´Jubileum´, while pollinizers ´R. C. Souffriau´ and ´Valor´ for the cultivar ´Reeves´. Cultivars ´Opal´, ´R. E. Prolific´ and ´Mallard´ are excellent pollinizers for ´Edda´ in conditions of higher temperatures during flowering period and post-flowering period. Cultivar ´Č. Lepotica´ proved to be the best pollinizer for ´Edda´ in conditions when the temperatures were lower. Cultivars ´Opal´ and ´R. E. Prolific´ can be considered as good pollinizers for ´Mallard´.
Sammendrag
The environmental sustainability of food production systems, including net greenhouse gas (GHG) emissions, is of increasing importance. In Norwegian pork production, animal performance is high in terms of reproduction, growth, and health. The development and use of an IPCC methodology-based model for estimating GHG emissions from pork production could be helpful in identifying the effects of progress in genetics and management. The objective was to investigate whether an IPCC methodology-based model was able to reflect the effects of the progress in genetics and management in pork production on the GHG emissions per kg carcass weight (CW). It is hypothesized that this progress has led to low GHG emissions intensities in Norwegian pork compared to global levels and that expected improvements will give a lasting reduction in GHG emissions intensities. A model ‘HolosNorPork’ for estimating net farm gate GHG emissions intensities was developed, including allocation procedures, at the pig production unit level. The model was run with pig production data from in average 632 farms from 2014 to 2019. The estimates include emissions of enteric and manure storage methane, manure storage nitrous oxide emissions, as well as GHG emissions from production and transportation of purchased feeds, and direct and indirect GHG emissions caused by energy use in pig-barns. The model was able to estimate the effects on net GHG emissions intensities from pork production on the basis of production characteristics. The estimated net GHG emissions intensity was found to have decreased from on average 2.49 to 2.34 kg CO2 eq. kg−1 CW over the investigated period. For 2019 the net GHG emission for the one-third lower performing farms was estimated to 2.56 kg CO2 eq. kg−1 CW, whereas for the one-third medium and one-third best performing farms the estimates were 2.36 and 2.16 kg CO2 eq. kg−1 CW, respectively. The net GHG emissions intensity for pork carcasses from boars was estimated to be 2.07 kg CO2 eq. kg−1 CW. For the health regimes investigated, Conventional and Specific-Pathogen Free (SPF), the estimated GHG emissions intensities for 2019 were 2.37 and 2.24 kg CO2 eq. kg−1 CW, respectively. The effects on net GHG emissions intensities of breeding and management measures were estimated to be profound, and this progress in pig production systems contributes to an on-going strengthening of pork as a sustainable source for human food supply.
Forfattere
Selamawit Araya Kidane Beira H. Meressa Solveig Haukeland Trine Hvoslef-Eide Danny L. CoyneSammendrag
Pratylenchus goodeyi appears to be the most prevalent nematode pest of enset in Ethiopia, where it can occur in extremely high densities. However, the damage to yield or how different enset cultivars react to the nematode has yet to be determined. The current study therefore sought to establish a first assessment of these reactions by enset to P. goodeyi infection. Determining pest resistant cultivars is an important task in developing management strategies. Our study evaluated nine enset cultivars to establish host response and identify potential sources of resistance. In addition, the pathogenicity of P. goodeyi was assessed on three enset cultivars. After 9 months’ growth, significant differences in final population densities (Pf) and reproduction factor (RF) were observed amongst the nine cultivars, with ‘Gefetanuwa’ the most susceptible (Pf = 25 799 and RF = 12.9), and similarly in a repeat experiment for 4.5 months (Pf = 126 534 and RF = 63.3). ‘Maziya’ and ‘Heila’ were the most resistant in the first experiment (Pf < 455 and RF < 0.2) as well as in the repeat, together with ‘Kellisa’ (Pf < 5255 and RF < 2.6). In the pathogenicity experiment four inoculum densities significantly affected the Pf and RF but not among the three cultivars ‘Maziya’, ‘Arkiya’ and ‘Heila’. This is the first known study to assess genotype reaction to P. goodeyi, which shows that there are significant differences in the reactions of different cultivars and that resistance appears to be present in enset.
Forfattere
Bjørn Egil FløSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
During a three-day field trip to the Gaupne area, Luster kommune, three main localities were visited in search of lichens. A total of 35 lichens or lichenicolous fungi were found to be new to Sogn og Fjordane, most of which are also rare on a national scale. Three species on rocks, Calogaya biatorina, Lecanora gisleriana and L. subaurea, are red-listed and two species, Blastenia monticola and Caloplaca squamuleoisidiata, are new to Norway. Most of the species new to Sogn og Fjordane are calcicolous or prefer siliceous rocks containing high levels of heavy metals. The area around Gaupne is shown to be a previously unknown lichen hot-spot.
Forfattere
Raquel Benavides Bárbara Carvalho Cristina C. Bastias David López-Quiroga Antonio Mas Stephen Cavers Alan Gray Audrey Albet Ricardo Alía Olivier Ambrosio Filippos Aravanopoulos Francisco Auñón Camilla Avanzi Evangelia V. Avramidou Francesca Bagnoli Eduardo Ballesteros Evangelos Barbas Catherine Bastien Frédéric Bernier Henry Bignalet Damien Bouic William Brunetto Jurata Buchovska Ana M. Cabanillas-Saldaña Nicolas Cheval José M. Climent Marianne Correard Eva Cremer Darius Danusevičius Benjamin Dauphin Fernando Del Caño Jean-Luc Denou Bernard Dokhelar Rémi Dourthe Anna-Maria Farsakoglou Andreas Fera Patrick Fonti Ioannis Ganopoulos José M. García del Barrio Olivier Gilg Santiago C González-Martínez René Graf Delphine Grivet Felix Gugerli Christoph Hartleitner Katrin Heer Enja Hollenbach Agathe Hurel Bernard Issehuth Florence Jean Veronique Jorge Arnaud Jouineau Jan-Philipp Kappner Katri Kärkkäinen Robert Kesälahti Florian Knutzen Sonja T. Kujala Timo Kumpula Mariaceleste Labriola Celine Lalanne Johannes Lambertz Martin Lascoux Gregoire Le Provost Mirko Liesebach Ermioni Malliarou Jérémy Marchon Nicolas Mariotte Elisabet Martínez-Sancho Silvia Matesanz Helge Meischner Célia Michotey Pascal Milesi Sandro Morganti Tor Myking Anne Eskild Nilsen Eduardo Notivol Lars Opgenoorth Geir Østreng Birte Pakull Andrea Piotti Christophe Plomion Nicolas Poinot Mehdi Pringarbe Luc Puzos Tanja Pyhäjärvi Annie Raffin José A Ramírez-Valiente Christian Rellstab Sebastian Richter Juan J Robledo-Arnuncio Sergio San Segundo Outi Savolainen Volker Schneck Silvio Schueler Ivan Scotti Vladimir Semerikov Jørn Henrik Sønstebø Ilaria Spanu Jean Thevenet Mari Mette Tollefsrud Norbert Turion Giovanni Giuseppe Vendramin Marc Villar Johan Westin Bruno Fady Fernando ValladaresSammendrag
Motivation Trait variation within species can reveal plastic and/or genetic responses to environmental gradients, and may indicate where local adaptation has occurred. Here, we present a dataset of rangewide variation in leaf traits from seven of the most ecologically and economically important tree species in Europe. Sample collection and trait assessment are embedded in the GenTree project (EU-Horizon 2020), which aims at characterizing the genetic and phenotypic variability of forest tree species to optimize the management and sustainable use of forest genetic resources. Our dataset captures substantial intra- and interspecific leaf phenotypic variability, and provides valuable information for studying the relationship between ecosystem functioning and trait variability of individuals, and the response and resilience of species to environmental changes. Main types of variable contained We chose morphological and chemical characters linked to trade-offs between acquisition and conservation of resources and water use, namely specific leaf area, leaf size, carbon and nitrogen content and their ratio, and the isotopic signature of stable isotope 13C and 15N in leaves. Spatial location and grain We surveyed between 18 and 22 populations per species, 141 in total, across Europe. Time period Leaf sampling took place between 2016 and 2017. Major taxa and level of measurement We sampled at least 25 individuals in each population, 3,569 trees in total, and measured traits in 35,755 leaves from seven European tree species, i.e. the conifers Picea abies, Pinus pinaster and Pinus sylvestris, and the broadleaves Betula pendula, Fagus sylvatica, Populus nigra and Quercus petraea. Software format The data files are in ASCII text, tab delimited, not compressed.
Forfattere
Lars Opgenoorth Benjamin Dauphin Raquel Benavides Katrin Heer Paraskevi Alizoti Elisabet Martínez-Sancho Ricardo Alía Olivier Ambrosio Albet Audrey Francisco Auñón Camilla Avanzi Evangelia Avramidou Francesca Bagnoli Evangelos Barbas Cristina C Bastias Catherine Bastien Eduardo Ballesteros Giorgia Beffa Frédéric Bernier Henri Bignalet Guillaume Bodineau Damien Bouic Sabine Brodbeck William Brunetto Jurata Buchovska Melanie Buy Ana M Cabanillas-Saldaña Bárbara Carvalho Nicolas Cheval José M Climent Marianne Correard Eva Cremer Darius Danusevičius Fernando Del Caño Jean-Luc Denou Nicolas Di Gerardi Bernard Dokhelar Alexis Ducousso Anne Eskild Nilsen Anna-Maria Farsakoglou Patrick Fonti Ioannis Ganopoulos José M. García del Barrio Olivier Gilg Santiago C González-Martínez René Graf Alan Gray Delphine Grivet Felix Gugerli Christoph Hartleitner Enja Hollenbach Agathe Hurel Bernard Issehut Florence Jean Veronique Jorge Arnaud Jouineau Jan-Philipp Kappner Katri Kärkkäinen Robert Kesälahti Florian Knutzen Sonja T Kujala Timo A Kumpula Mariaceleste Labriola Celine Lalanne Johannes Lambertz Martin Lascoux Vincent Lejeune Gregoire Le-Provost Joseph Levillain Mirko Liesebach David López-Quiroga Benjamin Meier Ermioni Malliarou Jérémy Marchon Nicolas Mariotte Antonio Mas Silvia Matesanz Helge Meischner Célia Michotey Pascal Milesi Sandro Morganti Daniel Nievergelt Eduardo Notivol Geir Østreng Birte Pakull Annika Perry Andrea Piotti Christophe Plomion Nicolas Poinot Mehdi Pringarbe Luc Puzos Tanja Pyhäjärvi Annie Raffin José A Ramírez-Valiente Christian Rellstab Dourthe Remi Sebastian Richter Juan J Robledo-Arnuncio Sergio San Segundo Outi Savolainen Silvio Schueler Volker Schneck Ivan Scotti Vladimir Semerikov Lenka Slámová Jørn Henrik Sønstebø Ilaria Spanu Jean Thevenet Mari Mette Tollefsrud Norbert Turion Giovanni Giuseppe Vendramin Marc Villar Georg von Arx Johan Westin Bruno Fady Tor Myking Fernando Valladares Filippos A Aravanopoulos Stephen CaversSammendrag
Background Progress in the field of evolutionary forest ecology has been hampered by the huge challenge of phenotyping trees across their ranges in their natural environments, and the limitation in high-resolution environmental information. Findings The GenTree Platform contains phenotypic and environmental data from 4,959 trees from 12 ecologically and economically important European forest tree species: Abies alba Mill. (silver fir), Betula pendula Roth. (silver birch), Fagus sylvatica L. (European beech), Picea abies (L.) H. Karst (Norway spruce), Pinus cembra L. (Swiss stone pine), Pinus halepensis Mill. (Aleppo pine), Pinus nigra Arnold (European black pine), Pinus pinaster Aiton (maritime pine), Pinus sylvestris L. (Scots pine), Populus nigra L. (European black poplar), Taxus baccata L. (English yew), and Quercus petraea (Matt.) Liebl. (sessile oak). Phenotypic (height, diameter at breast height, crown size, bark thickness, biomass, straightness, forking, branch angle, fructification), regeneration, environmental in situ measurements (soil depth, vegetation cover, competition indices), and environmental modeling data extracted by using bilinear interpolation accounting for surrounding conditions of each tree (precipitation, temperature, insolation, drought indices) were obtained from trees in 194 sites covering the species’ geographic ranges and reflecting local environmental gradients. Conclusion The GenTree Platform is a new resource for investigating ecological and evolutionary processes in forest trees. The coherent phenotyping and environmental characterization across 12 species in their European ranges allow for a wide range of analyses from forest ecologists, conservationists, and macro-ecologists. Also, the data here presented can be linked to the GenTree Dendroecological collection, the GenTree Leaf Trait collection, and the GenTree Genomic collection presented elsewhere, which together build the largest evolutionary forest ecology data collection available.
Forfattere
Hannes Müller Schmied Denise Caceres Stephanie Eisner Martina Flörke Claudia Herbert Christoph Niemann Thedini Asali Peiris Eklavyya Popat Felix Theodor Portmann Robert Reinecke Maike Schumacher Somayeh Shadkam Camelia-Eliza Telteu Tim Trautmann Petra DöllSammendrag
WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water resources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future, in particular under climate change. It has improved our understanding of continental water storage variations, with a focus on overexploitation and depletion of water resources. In this paper, we describe the most recent model version WaterGAP 2.2d, including the water use models, the linking model that computes net abstractions from groundwater and surface water and the WaterGAP Global Hydrology Model (WGHM). Standard model output variables that are freely available at a data repository are explained. In addition, the most requested model outputs, total water storage anomalies, streamflow and water use, are evaluated against observation data. Finally, we show examples of assessments of the global freshwater system that can be achieved with WaterGAP 2.2d model output.