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
Det er ikke registrert sammendrag
Rapport – Rekartlegging av kystlynghei på Svinøya, Nærøysund kommune, Trøndelag fylke
Synnøve Grenne
Forfattere
Synnøve GrenneSammendrag
Denne rapporten presenterer rekartlegging og verdisetting av naturtyper, spesielt med hensyn til kystlynghei og strandeng på Svinøya i Nærøysund kommune, Trøndelag fylke, på oppdrag fra Nærøysund kommune. Målsettingen med arbeidet var å få en rekartlegging av kystlyngheien på Svinøya etter NiN, samt en kort, overordnet vurdering av lokalitetene etter DN-håndbok 13.
Forfattere
Synnøve GrenneSammendrag
Denne rapporten presenterer revidert skjøtselsplan for kystlynghei for lokaliteten Madsøya i Ørland kommune, på oppdrag fra grunneier og bruker Bente Haugen Madsø og Statsforvalteren i Trøndelag. Skjøtselsplanen er en revidering av planen fra 2015 utarbeidet av Olaug Bach (Bach O. 2015). Skjøtselsplanen er utarbeidet etter mal for skjøtselsplaner for kystlynghei i regi av Miljødirektoratet. Kartleggingen av Madsøya har følgt Miljødirektoratets kartleggingsinstruks (MD 2021). I forbindelse med arbeidet ble Madsøya rekartlagt etter NiN 2.1 og kystlyngheien fikk dermed ny avgrensing, områdebeskrivelse og verdisetting.
Sammendrag
Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. While most often used for modeling species, distribution modeling methods can also be applied to vegetation types. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. The paper compares the performance of three methods for assembling predictions for multiple vegetation types, modeled individually, into a wall-to-wall map. The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. Thus the assembly methods worked in two principally different ways: the probability-based method assigned vegetation types to grid cells in a cell-by-cell manner, and both the performance-based method and prevalence-based method assigned them in a type-by-type manner. All methods were evaluated by use of reference data collected in the field, more or less independently of the data used to parameterize the vegetation-type models. Quantity, allocation, and total disagreement, as well as proportional dissimilarity metrics, were used for evaluation of assembly methods. Overlay analysis showed 38.1% agreement between all three assembly methods. The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics. The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved. area frame survey, assembly strategies, distribution modeling, spatial probabilities, vegetation mapping, vegetation types
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
Christian Brischke Gry Alfredsen Miha Humar Elena Conti Laurie Cookson Lukas Emmerich Per Otto Flæte Stefania Fortino Lesley Francis Ulrich Hundhausen Ilze Irbe Kordula Jacobs Morten Klamer Davor Krzisnik Bostjan Lesar Eckhard Melcher Linda Meyer-Veltrup Jeffrey J. Morrell Jack Norton Sabrina Palanti Gerald Presley Ladislav Reinprecht Tripti Singh Rod Stirling Martti Venäläinen Mats Westin Andrew H. H. Wong Ed SuttieSammendrag
Durability-based designs with timber require reliable information about the wood properties and how they affect its performance under variable exposure conditions. This study aimed at utilizing a material resistance model (Part 2 of this publication) based on a dose–response approach for predicting the relative decay rates in above-ground situations. Laboratory and field test data were, for the first time, surveyed globally and used to determine material-specific resistance dose values, which were correlated to decay rates. In addition, laboratory indicators were used to adapt the material resistance model to in-ground exposure. The relationship between decay rates in- and above-ground, the predictive power of laboratory indicators to predict such decay rates, and a method for implementing both in a service life prediction tool, were established based on 195 hardwoods, 29 softwoods, 19 modified timbers, and 41 preservative-treated timbers.
Forfattere
Yagut Allahverdiyeva Eva-Mari Aro Bert van Bavel Carlos Escudero-Oñate Christiane Funk Jarna Heinonen Lars Herfindal Peter Lindblad Sari Makinen Merja Penttilä Kaarina Sivonen Matilde Skogen Chauton Hanne Skomedal Jorunn SkjermoSammendrag
NordAqua is a multidisciplinary Nordic Center of Excellence funded by NordForsk Bioeconomy program (2017–2022). The research center promotes Blue Bioeconomy and endeavours to reform the use of natural resources in a environmentally sustainable way. In this short communication, we summarize particular outcomes of the consortium. The key research progress of NordAqua includes (1) improving of photosynthetisis, (2) developing novel photosynthetic cell factories that function in a “solar-driven direct CO2 capture to target bioproducts” mode, (3) promoting the diversity of Nordic cyanobacteria and algae as an abundant and resilient alternative for less sustainable forest biomass and for innovative production of biochemicals, and (4) improving the bio-based wastewater purification and nutrient recycling technologies to provide new tools for integrative circular economy platforms.
Sammendrag
Current forage production on tile drained peat soil is challenged by low drainage efficiency and large GHG emissions. Alternative methods need to be evaluated to sustain agricultural usage while protecting peat C and N stocks. Peat inversion is a valid method when the peat layer is less than 1.5 m deep and lies on top of a self-draining mineral soil. The peat body is covered by the underlying mineral soil while maintaining connectivity to the self-draining subsoil through tilted mineral soil layers. We studied the effect of inversion of previously tile drained peat with forage production on dry matter yield (DMY), methane (CH4) and nitrous oxide (N2O) emissions and peat degradation. The field experiment was carried out in adjacent fields with inverted and tile drained nutrient poor peat in Western Norway during 2014-2018. At both fields the surface was slightly graded towards open ditches surrounding the field. The thickness of the mineral cover layer of the inverted peat varied between 80-100 cm on top of the graded surface (upper site) and 40-50 cm closer to the ditches (lower site). Coarse silt and fine sand dominated the texture of the cover layer and content of organic matter was very low (0.5 % tot. C). The texture was finer (higher content of silt and clay) at the lower site compared to the upper site. Mean DMY for 4 ley years at the inverted (upper site) and tile drained peat was 12.2 and 10.3 t ha-1 y-1, respectively. Mean methane emissions in tile drained peat were 200, 140, 209 and 55 kg CH4-C ha-1 in 2015, 2016, 2017 and 2018, respectively, whereas the CH4 exchange in inverted peat was small. In inverted peat, we found up to 50 vol% CH4 in the soil air close to the buried peat, which strongly decreased towards the soil surface at both inverted sites. Nitrous oxide emissions in fertilized tile drained peat were 4.3, 9.5, 9.8 and 5.3 kg N2O-N ha-1 in 2015-2018, respectively. In inverted peat (upper site) N2O emissions were 3.6, 3.6, 8.5 and 2.7 kg N2O-N ha-1 these years. In lower site, measured in 2017 and 2018, the emissions were 10.3 and 4.5 kg N2O-N ha-1, respectively for the two years. N2O-emissions were small in unfertilized plots both at tile drained and inverted peat. Depth profiles of N2O in soil air indicated that N2O is produced in the mineral layer and not in the buried peat. Continuously monitored O2 profiles showed O2-concentrations of 0-5 vol% in the top of the buried peat and much higher concentrations (5-20 vol %) in the tile drained peat. Dark chamber measurements in 2018 showed a CO2-flux of 1.43, 1.49 and 2.35 kg ha-1 h-1 CO2-C after 1.st cut and 1.4, 1.25 and 2.01 kg ha-1 h-1 CO2-C after 2.cut in inverted upper site, inverted lower site and tile drained peat, respectively. The larger respiration measured at tile drained peat most probably derives from larger heterotrophic respiration, as the mass of roots was lower in tile drained than in inverted peat. Results from this field experiment suggest that inversion of tile drained peat reduces the CH4 emissions and degradation of the peat. N2O emissions is fertilizer induced in both tile drained and inverted nutrient poor peat, and is determined by soil and weather conditions at the time of fertilization. The large variation in emissions between years can be explained by different weather conditions. 2017 was a wet year and 2018 a very dry year.
Sammendrag
The separate and synergistic effects of land use and climate change on water quality variables in Old Woman Creek (OWC) watershed were evaluated using a hydrological model set up in Soil and Water Assessment Tool (SWAT) for the OWC watershed. Model calibration was done using a multi-objective evolutionary algorithm and pareto optimization. The Parameter-Elevation Regressions on Independent Slopes Model (PRISM) climate data and the 20 different Global Circulation Models (GCMs) developed by the Coupled Model Intercomparison Project Phase five (CMIP5) were used. Validation was done using the streamflow data from USGS gaging station and water quality data from the water quality lab, Heidelberg University. The simulation was divided into two land use scenarios: Scenario 1 for constant land use and Scenario 2 where land use was varied. Both land use simulations were run in four time periods to account for climate change: historical (1985–2014), current to near future (2018–2045), mid-century (2046–2075), and late-century (2076–2100) climate windows. For the historical period, the average of all the simulations made from the 20 different CMIP5 GCMs shows good agreement with the PRISM results for flow and the water quality variables of interest with smaller inter-model variability compared to PRISM results. For the other three climate windows, the results of Scenario 1 show an increase in flow and eight water quality variables (sediment (total suspended sediment), organic nitrogen, organic phosphorus (particulate p), mineral phosphorus (soluble reactive p), chlorophyll a, carbonaceous biochemical oxygen demand (CBOD), dissolved oxygen, total nitrogen) across the climate windows but a slight decrease in one water quality variable, mineral phosphorus in the mid-century. The results of Scenario 2 show a greater increase in flow, and the eight water quality variables across the climate windows show a relatively larger decrease in one water quality variable (mineral phosphorus). The projected land use change has little impact compared to the projected climate change on OWC watershed in the 21st century.
Forfattere
Carla Cruz-Paredes Tomas Diera Marie Louise Davey Maria Monrad Rieckmann Peter Christensen Majbrit Dela Cruz Kristian Holst Laursen Erik J. Joner Jan H. Christensen Ole Nybroe Iver JakobsenSammendrag
Arbuscular mycorrhizal fungi (AMF) are important in plant nutrient uptake, but their function is prone to environmental constraints including soil factors that may suppress AMF transfer of phosphorus (P) from the soil to the plant. The objective of this study was to disentangle the biotic and abiotic components of AMF-suppressive soils. Suppression was measured in terms of AMF-mediated plant uptake of 33P mixed into a patch of soil and treatments included soil sterilization, soil mixing, pH manipulation and inoculation with isolated soil fungi. The degree of suppression was compared to volatile organic compound (VOC) production by isolated fungi and to multi-element analysis of soils. For a selected suppressive soil, sterilization and soil mixing experiments confirmed a biotic component of suppression. A Fusarium isolate from that soil suppressed the AMF activity and produced greater amounts than other fungal isolates of the antimicrobial VOC trichodiene (a trichothecene toxin precursor), beta-chamigrene, alpha-cuprenene and p-xylene. These metabolites deserve further attention when unravelling the chemical background behind the suppression of AMF activity by soil microorganisms. For the abiotic component of suppression, soil liming and acidification experiments confirmed that suppression was strongest at low pH. The pH effect might be associated with changed availability of specific suppressive elements. Indeed 33P uptake from the soil patches correlated negatively to Al levels and Al toxicity seems to play a major role in the AMF suppressiveness at pH below 5.0–5.2. However, the documentation of a biotic component of suppression for both low and high pH soils leads to the conclusion that biotic and abiotic components of suppression may act in parallel in some soils. The current insight into the components of soil suppressiveness of the AMF activity aids to develop management practices that allow for optimization of AMF functionality.