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.
2022
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Zhanjiang Pei Shujun Liu Zhangmu Jing Yi Zhang Jingtian Wang Jie Liu Yajing Wang Wenyang Guo Yeqing Li Lu Feng Hongjun Zhou Guihua Li Yongming Han Di Liu Junting PanSammendrag
Det er ikke registrert sammendrag
Forfattere
Emily Lines Matthew Allen Carlos Cabo Kim Calders Amandine Debus Stuart Grieve Milto Miltiadou Adam Noach Harry JF Owen Stefano PulitiSammendrag
With the rise in high resolution remote sensing technologies there has been an explosion in the amount of data available for forest monitoring, and an accompanying growth in artificial intelligence applications to automatically derive forest properties of interest from these datasets. Many studies use their own data at small spatio-temporal scales, and demonstrate an application of an existing or adapted data science method for a particular task. This approach often involves intensive and time-consuming data collection and processing, but generates results restricted to specific ecosystems and sensor types. There is a lack of widespread acknowledgement of how the types and structures of data used affects performance and accuracy of analysis algorithms. To accelerate progress in the field more efficiently, benchmarking datasets upon which methods can be tested and compared are sorely needed.Here, we discuss how lack of standardisation impacts confidence in estimation of key forest properties, and how considerations of data collection need to be accounted for in assessing method performance. We present pragmatic requirements and considerations for the creation of rigorous, useful benchmarking datasets for forest monitoring applications, and discuss how tools from modern data science can improve use of existing data. We list a set of example large-scale datasets that could contribute to benchmarking, and present a vision for how community-driven, representative benchmarking initiatives could benefit the field.
Sammendrag
Tree-killing bark beetles in conifer forests vector symbiotic fungi that are thought to help the beetles kill trees. Fungal symbionts emit diverse volatile blends that include bark beetle semiochemicals involved in mating and host localization. In this study, all 12 tested fungal isolates emitted beetle semiochemicals when growing in medium amended with linoleic acid. These semiochemicals included the spiroacetals chalcogran, trans-conophthorin and exo-brevicomin, as well as 2-methyl-3-buten-1-ol, the main aggregation pheromone component of the spruce bark beetle Ips typographus. The emission of these compounds was affected by the type of fatty acid present (linoleic vs. oleic acid). Accumulating evidence shows that the fatty acid composition in conifer bark can facilitate colonization by bark beetles and symbiotic fungi, whereas the fatty acid composition of non-host trees can be detrimental for beetle larvae or fungi. We hypothesize that beetles probe the fatty acid composition of potential host trees to test their suitability for beetle development and release of semiochemicals by symbiotic fungi.
Forfattere
Johannes Schumacher Håvard Toft Larsen Paul McLean Marius Hauglin Rasmus Astrup Johannes BreidenbachSammendrag
The number of people affected by snow avalanches during recreational activities has increased over the recent years. An instrument to reduce these numbers are improved terrain classification systems. One such system is the Avalanche Terrain Exposure Scale (ATES). Forests can provide some protection from avalanches, and information on forest attributes can be incorporated into avalanche hazard models such as the automated ATES model (AutoATES). The objectives of this study were to (i) map forest stem density and canopy-cover based on National Forest Inventory and remote sensing data and, (ii) use these forest attributes as input to the AutoATES model. We predicted stem density and directly calculated canopy-cover in a 20 Mha study area in Norway. The forest attributes were mapped for 16 m × 16 m pixels, which were used as input for the AutoATES model. The uncertainties of the stem number and canopy-cover maps were 30% and 31%, respectively. The overall classification accuracy of 52 ski-touring routes in Western Norway with a total length of 282 km increased from 55% in the model without forest information to 67% when utilizing canopy cover. The F1 score for the three predicted ATES classes improved by 31%, 9%, and 6%.
Sammendrag
Norsk institutt for bioøkonomi utførte somrene 2019, 2020 og 2021 vegetasjonskartlegging i Lordalen i Lesja kommune. I denne rapporten sammenstilles resultatene fra dette arbeidet som omfatter 205 km². Kartlegginga er gjort etter instruks for kartlegging i målestokk 1:20 000–50 000 (VK25). Det er laga vegetasjonskart og 2 avleda temakart for beite for sau og storfe. Denne rapporten beskriver metoden for kartlegging, registrerte vegetasjonstyper og deres fordeling i området. Det er gitt en omtale av beiteverdi og beitekapasitet, og noen råd til skjøtsel av kulturlandskap og beite i kartområdet. The vegetation types over a total of 205 km2 in Lesja municipality have been mapped according to the methodology for vegetation mapping (scale 1:20 000–50 000). A vegetation map has been produced, from which 2 different thematic maps have been derived. This report describes the methodology and gives a detailed description of the registered vegetation types and their distribution in the area. Further, a description of other information which could be derived from the vegetation map is provided, with emphasis on grazing conditions for domestic animals.
Forfattere
Alexandra Kruse Hans Renes Goran Andlar Csaba Centeri Sebastian Eiter Viviana Ferrario Della Hooke Zdenek Kucera Oskar Puschmann Maurizia Sigura Martina Slámová Mateja Šmid Hribar Jana Spulerova Filip Srajer Dagmar Štefunková Mimi Urbanc Bénédicte GaillardSammendrag
Det er ikke registrert sammendrag
Forfattere
P.H. Templer J.L. Harrison Francesca Pilotto A. Flores-Díaz P. Haase W.H. McDowell R. Sharif H. Shibata D. Blankman A. Avila U. Baatar H.R. Bogena I. Bourgeois J. Campbell T. Dirnböck W.K. Dodds Marit Hauken I. Kokorite K. Lajtha I.-L. Lai H. Laudon T.C. Lin S.R.M. Lins H. Meesenburg P. Pinho A. Robison M. Rogora B. Scheler P. Schleppi R. Sommaruga T. Staszewski M. TakaSammendrag
Previous studies have evaluated how changes in atmospheric nitrogen (N) inputs and climate affect stream N concentrations and fluxes, but none have synthesized data from sites around the globe. We identified variables controlling stream inorganic N concentrations and fluxes, and how they have changed, by synthesizing 20 time series ranging from 5 to 51 years of data collected from forest and grassland dominated watersheds across Europe, North America, and East Asia and across four climate types (tropical, temperate, Mediterranean, and boreal) using the International Long-Term Ecological Research Network. We hypothesized that sites with greater atmospheric N deposition have greater stream N export rates, but that climate has taken a stronger role as atmospheric deposition declines in many regions of the globe. We found declining trends in bulk ammonium and nitrate deposition, especially in the longest time-series, with ammonium contributing relatively more to atmospheric N deposition over time. Among sites, there were statistically significant positive relationships between (1) annual rates of precipitation and stream ammonium and nitrate fluxes and (2) annual rates of atmospheric N inputs and stream nitrate concentrations and fluxes. There were no significant relationships between air temperature and stream N export. Our long-term data shows that although N deposition is declining over time, atmospheric N inputs and precipitation remain important predictors for inorganic N exported from forested and grassland watersheds. Overall, we also demonstrate that long-term monitoring provides understanding of ecosystems and biogeochemical cycling that would not be possible with short-term studies alone.
Sammendrag
European ash (Fraxinus excelsior) and narrow-leafed ash (F. angustifolia) are keystone forest tree species with a broad ecological amplitude and significant economic importance. Besides global warming both species are currently under significant threat by an invasive fungal pathogen that has been spreading progressively throughout the continent for almost three decades. Ash dieback caused by the ascomycete Hymenoscyphus fraxineus is capable of damaging ash trees of all age classes and often ultimately leads to the death of a tree after years of progressively developing crown defoliation. While studies at national and regional level already suggested rapid decline of ash populations as a result of ash dieback, a comprehensive survey at European level with harmonized crown assessment data across countries could shed more light into the population decline from a pan-European perspective and could also pave the way for a new conservation strategy beyond national boarders. Here we present data from the ICP Forests Level I crown condition monitoring from 27 countries resulting in > 36,000 observations. We found a substantial increase in defoliation and mortality over time indicating that crown defoliation has almost doubled during the last three decades. Hotspots of mortality are currently situated in southern Scandinavia and north-eastern Europe. Overall survival probability after nearly 30 years of infection has already reached a critical value of 0.51, but with large differences among regions (0.20–0.86). Both a Cox proportional hazard model as well as an Aalen additive regression model strongly suggest that survival of ash is significantly lower in locations with excessive water regime and which experienced more extreme precipitation events during the last two decades. Our results underpin the necessity for fast governmental action and joint rescue efforts beyond national borders since overall mean defoliation will likely reach 50% as early as 2030 as suggested by time series forecasting.
Sammendrag
In total, 154 wild raspberry samples were collected from 26 localities representing a large area in Norway (21 localities) and a narrowly defined region of the Giant Mountains in the northern parts of the Czech Republic (5 localities). The samples were characterized for genetic diversity and population differentiation as well as for their potential use in crop breeding. Choice of plant material was based on the biogeographical similarity between the Giant Mountains and relevant areas in Norway, where plant communities may have evolved in parallel since the ice ages. The overall level of genetic diversity ĥ = 0.786, I = 2.153 was high. Numerous rare alleles were found for raspberries originating especially from the East Giant Mountains populations Jeleni louky and Krakonosuv lom. The overall degree of population subdivision measured by Wright’s fixation index (FST) was of a moderate level of 0.28. The highest level 0.33 was found between populations in Northern Norway and 0.31 between populations in the Giant Mountains. The genetic structure was evaluated using Bayesian analyses as implemented using STRUCTURE software. According to the ΔK value, eight clusters (K8) were identified among all the analysed samples. The results of the analysis of molecular variance (AMOVA) indicated that 79.7% of the total variation could be attributed to differences among individuals within populations, 15.3% was credited to differences among populations within regions, and only 5.0% was attributed to differences among regions. We concluded based on the results that Czech and Norwegian raspberry (R. idaeus) populations growing in natural high altitude and northern ecosystems are important genetic resources and represent a valuable source of genes and unique allele compositions for in situ and ex situ conservation and future raspberry breeding programmes.