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
Forfattere
Gry Alfredsen Christian Brischke Brendan N. Marais Robert F. A. Stein Katrin Zimmer Miha HumarSammendrag
To evaluate the performance of new wood-based products, reference wood species with known performances are included in laboratory and field trials. However, different wood species vary in their durability performance, and there will also be a within-species variation. The primary aim of this paper was to compare the material resistance against decay fungi and moisture performance of three European reference wood species, i.e., Scots pine sapwood (Pinus sylvestris), Norway spruce (Picea abies), and European beech (Fagus sylvatica). Wood material was collected from 43 locations all over Europe and exposed to brown rot (Rhodonia placenta), white rot (Trametes versicolor) or soft rot fungi. In addition, five different moisture performance characteristics were analyzed. The main results were the two factors accounting for the wetting ability (kwa) and the inherent protective properties of wood (kinh), factors for conversion between Norway spruce vs. Scots pine sapwood or European beech for the three decay types and four moisture tests, and material resistance dose (DRd) per wood species. The data illustrate that the differences between the three European reference wood species were minor, both with regard to decay and moisture performance. The results also highlight the importance of defined boundaries for density and annual ring width when comparing materials within and between experiments. It was concluded that with the factors obtained, existing, and future test data, where only one or two of the mentioned reference species were used, can be transferred to models and prediction tools that use another of the reference species
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.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Johannes Breidenbach Ronald E. McRoberts Iciar Alberdi Clara Antón Fernández Erkki TomppoSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
I 2019 vedtok Stortinget innføring av individmerking av rein. I vedtaket forutsettes det at dette ikke gjennomføres før praktiske og tekniske løsninger er på plass. Videre slås det fast at tradisjonelle eiermerker (snitt i ørene) skal videreføres. Norsk institutt for bioøkonomi (NIBIO) har tidligere gjort forsøk med å kombinere tradisjonelle eiermerker med elektronisk merker basert på RFID-teknologi. I denne POP’en kan du lese om erfaringene med dette.
Forfattere
Stefano Puliti Grant D. Pearse Michael S. Watt Edward Mitchard Ian McNicol Magnus Bremer Martin Rutzinger Peter Surovy Luke Wallace Markus Hollaus Rasmus AstrupSammendrag
Survey-grade laser scanners suitable for drones (UAV-LS) allow the efficient collection of finely detailed three-dimensional (3D) information on tree structures allowing to resolve the complexity of the forest into discrete individual trees and species as well as into different component of the tree. Current developments are hindered by the limited availability of survey-grade UAV-LS data and by the lack of a publicly available benchmark dataset for developing and validating methods. We present a new benchmarking dataset composed of manually labelled UAV-LS data covering forests in different continents and eco-regions. Such data consists in single-tree point clouds, with each point classified as either stem, branches, and leaves. This benchmark dataset offers new possibilities to develop single-tree segmentation algorithms and validate existing ones.
Forfattere
Stefano Puliti Grant Pearse Michael Watt Edward Mitchard Ian McNicol Magnus Bremer Martin Rutzinger Peter Surovy Luke Wallace Markus Hollaus Rasmus AstrupSammendrag
Det er ikke registrert sammendrag
Sammendrag
There is a need for mapping of forest areas with young stands under regeneration in Norway, as a basis for conducting tending, or precommercial thinning (PCT), whenever necessary. The main objective of this article is to show the potential of multitemporal Sentinel-1 (S-1) and Sentinel-2 (S-2) data for characterization and detection of forest stands under regeneration. We identify the most powerful radar and optical features for discrimination of forest stands under regeneration versus other forest stands. A number of optical and radar features derived from multitemporal S-1 and S-2 data were used for the class separability and cross-correlation analysis. The analysis was performed on forest resource maps consisting of the forest development classes and age in two study sites from south-eastern Norway. Important features were used to train the classical random forest (RF) classification algorithm. A comparative study of performance of the algorithm was used in three cases: I) using only S-1 features, II) using only S-2 optical bands, and III) using combination of S-1 and S-2 features. RF classification results pointed to increased class discrimination when using S-1 and S-2 data in relation to S-1 or S-2 data only. The study shows that forest stands under regeneration in the height interval for PCT can be detected with a detection rate of 91% and F-1 score of 73.2% in case III as most accurate, while tree density and broadleaf fraction could be estimated with coefficient of determination ( R2 ) of about 0.70 and 0.80, respectively.