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.
2016
Forfattere
Kjersti Holt HanssenSammendrag
Det er ikke registrert sammendrag
Forfattere
Kjersti Holt HanssenSammendrag
Det er ikke registrert sammendrag
Forfattere
Kjersti Holt HanssenSammendrag
Det er ikke registrert sammendrag
Forfattere
Kjersti Holt HanssenSammendrag
Det er ikke registrert sammendrag
Forfattere
Mathias Neumann Adam Moreno Volker Mues Sanna Härkönen Matteo Mura Olivier Bouriaud Mait Lang Wouter M.J. Achten Alain Thivolle-Cazat Karol Bronisz Jan Merganič Mathieu Decuyper Iciar Alberdi Rasmus Astrup Frits Mohren Hubert HasenauerSammendrag
National and international carbon reporting systems require information on carbon stocks of forests. For this purpose, terrestrial assessment systems such as forest inventory data in combination with carbon estimation methods are often used. In this study we analyze and compare terrestrial carbon estimation methods from 12 European countries. The country-specific methods are applied to five European tree species (Fagus sylvatica L., Quercus robur L., Betula pendula Roth, Picea abies (L.) Karst. and Pinus sylvestris L.), using a standardized theoretically-generated tree dataset. We avoid any bias due to data collection and/or sample design by using this approach. We are then able to demonstrate the conceptual differences in the resulting carbon estimates with regard to the applied country-specific method. In our study we analyze (i) allometric biomass functions, (ii) biomass expansion factors in combination with volume functions and (iii) a combination of both. The results of the analysis show discrepancies in the resulting estimates for total tree carbon and for single tree compartments across the countries analyzed of up to 140 t carbon/ha. After grouping the country-specific approaches by European Forest regions, the deviation within the results in each region is smaller but still remains. This indicates that part of the observed differences can be attributed to varying growing conditions and tree properties throughout Europe. However, the large remaining error is caused by differences in the conceptual approach, different tree allometry, the sample material used for developing the biomass estimation models and the definition of the tree compartments. These issues are currently not addressed and require consideration for reliable and consistent carbon estimates throughout Europe.
Sammendrag
Individual tree mortality models based on logistic regression exist for different tree species and countries around the world. We examine two mortality models developed in Norway and two models from Austria for Norway spruce (Picea abies), Scots pine (Pinus sylvestris) and birch (Betula pubescens and Betula pendula) trees. We apply all models with their original coefficients on the Norwegian National Forest Inventory (NNFI) data. The dataset comprises 36,217 spruce, 17,483 pine and 24,418 birch trees. We show the differences in predictions that arise from newly paramete-rized predictor variables and the effect of the original calibration data from different geographic regions. Next we recalibrate the mortality functions with the NNFI data to show the improvements in the predictions and illustrate the impact of the different predictor variables. We apply statistical methods to assess which of the original and recalibrated models best mimic the observed mortality rates of the three species. Finally we provide the new coefficient set for the model functions for spruce, pine and birch in Norway.
Forfattere
Mathias Neumann Adam Moreno Christopher Thurnher Volker Mues Sanna Härkönen Matteo Mura Olivier Bouriaud Mait Lang Giuseppe Cardellini Alain Thivolle-Cazat Karol Bronisz Jan Merganic Iciar Alberdi Rasmus Astrup Frits Mohren Maosheng Zhao Hubert HasenauerSammendrag
Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.
Sammendrag
We demonstrate the efficacy of using close-range photogrammetry from a consumer grade camera as a tool in generating high-resolution, three-dimensional coloured point clouds for detailed analysis or monitoring of wheel ruts. Ground-based timber harvesting results in vehicle traffic on 12–70 per cent of the site, depending on the system used, with a variable probability of causing detrimental soil disturbance depending on climatic, hydrological and soil conditions at the time of harvest. Applying the technique described in this article can reduce the workload associated with the conventional manual measurement of wheel ruts, while providing a greatly enhanced source of information that can be used in analysing both physical and biological impact, or stored in a repository for later operation management or monitoring. Approaches for deriving and quantifying properties such as rut depths and soil displacement volumes are also presented. In evaluating the potential for widespread adoption of the method among forest or environmental managers, the study also presents the workflow and provides a comparison of the ease of use and quality of the results obtained from one commercial and two open source image processing software packages. Results from a case study showed no significant difference between packages on point cloud quality in terms of model distortion. Comparison of photogrammetric profiles against profiles measured manually resulted in root mean square errors of between 2.07 and 3.84 cm for five selected road profiles. Maximal wheel rut depth for three different models were 1.15, 0.99 and 1.01 m, and estimated rut volumes were 9.84, 9.10 and 9.09 m3, respectively, for 22.5 m long sections.
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Sustainable forest management in an era of global changes has always been a central thematic area for the International Boreal Forest Research Association (IBFRA). At the 17th IBFRA conference held on 24–29 May 2015 in Rovaniemi, Finland, the theme of global change was accompanied by a new theme related to the use and value of big data in boreal forest management and research. Keynote presentations had a clear message that sustainably managed boreal forests and peatlands play a significant role in climate change mitigation. However, the choice of the most efficient mitigation options will vary with regional differences in ecology, institutional strength, and management intensity. In addition to changes in greenhouse gas fluxes linked to ecosystem dynamics, the design of climate change mitigation strategies should also account for the fate of harvested wood products and for the substitution of more energy-intensive materials such as concrete and steel. For climate change mitigation, it is therefore not only forest management that matters, but also ensuring the best possible end use for the produced biomass. Key note presentations on use and value of big data in the forest sector demonstrated the role of time series of remote sensing data in forest monitoring and research. In addition, new technologies and methods including terrestrial laser scanning are starting to provide detailed three-dimensional information from forest stands from which management tools and scientific understanding will be developed. Finally, citizen science was shown to offer a vast potential for the generation of forest-based data. Thus, new means are being developed by which forest scientists and managers will be able to obtain new, more frequent, and more detailed information on the forest. The ensuing development of knowledge will benefit the forest sector, create new opportunities for furthering boreal forest science, and finally benefit the society as a whole...