Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2016
Authors
Yoshiaki Tsuda Jun Chen Michael Stocks Thomas Källman Jørn Henrik Sønstebø Laura Parducci Vladimir Semerikov Christoph Sperisen Dmitry Politov Tiina Ronkainen Minna Väliranta Giovanni Giuseppe Vendramin Mari Mette Tollefsrud Martin LascouxAbstract
Boreal species were repeatedly exposed to ice ages and went through cycles of contraction and expansion while sister species alternated periods of contact and isolation. The resulting genetic structure is consequently complex, and demographic inferences are intrinsically challenging. The range of Norway spruce (Picea abies) and Siberian spruce (Picea obovata) covers most of northern Eurasia; yet their geographical limits and histories remain poorly understood. To delineate the hybrid zone between the two species and reconstruct their joint demographic history, we analysed variation at nuclear SSR and mitochondrial DNA in 102 and 88 populations, respectively. The dynamics of the hybrid zone was analysed with approximate Bayesian computation (ABC) followed by posterior predictive structure plot reconstruction and the presence of barriers across the range tested with estimated effective migration surfaces. To estimate the divergence time between the two species, nuclear sequences from two well-separated populations of each species were analysed with ABC. Two main barriers divide the range of the two species: one corresponds to the hybrid zone between them, and the other separates the southern and northern domains of Norway spruce. The hybrid zone is centred on the Urals, but the genetic impact of Siberian spruce extends further west. The joint distribution of mitochondrial and nuclear variation indicates an introgression of mitochondrial DNA from Norway spruce into Siberian spruce. Overall, our data reveal a demographic history where the two species interacted frequently and where migrants originating from the Urals and the West Siberian Plain recolonized northern Russia and Scandinavia using scattered refugial populations of Norway spruce as stepping stones towards the west.
Authors
Riikka Linnakoski Robert Jankowiak Caterina Villari Thomas Kirisits Halvor Solheim Z. Wilhelm de Beer Michael J. WingfieldAbstract
Two species of blue-stain fungi with similar morphologies, Ophiostoma brunneo-ciliatum and Ophiostoma clavatum, are associates of bark beetles infesting Pinus spp. in Europe. This has raised questions whether they represent distinct taxa. Absence of herbarium specimens and contaminated or mistakenly identified cultures of O. brunneo-ciliatum and O. clavatum have accentuated the uncertainty regarding their correct identification. The aim of this study was to reconsider the identity of European isolates reported as O. brunneo-ciliatum and O. clavatum by applying DNA-based identification methods, and to provide appropriate type specimens for them. Phylogenetic analyses of the ITS, βT, TEF-1α and CAL gene sequences revealed that the investigated isolates represent a complex of seven cryptic species. The study confirmed that ITS data is insufficient to delineate species in some Ophiostoma species clusters. Lectotypes and epitypes were designated for O. clavatum and O. brunneo-ciliatum, and three new species, Ophiostoma brunneolum, Ophiostoma macroclavatum and Ophiostoma pseudocatenulatum, are described in the newly defined O. clavatum-complex. The other two species included in the complex are Ophiostoma ainoae and Ophiostoma tapionis. The results suggest co-evolution of these fungi in association with specific bark beetles. The results also confirm the identity of the fungus associated with the pine bark beetle Ips acuminatus as O. clavatum, while O. brunneo-ciliatum appears to be mainly associated with another pine bark beetle, Ips sexdentatus.
Authors
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 HasenauerAbstract
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.
Abstract
Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway.
Authors
Hans Estrup Andersen Gitte Blicher-Mathiesen Hans Thodsen Peter Mejlhede Andersen Søren E. Larsen Per Stålnacke Christoph Humborg Carl-Magnus Mörth Erik SmedbergAbstract
Agricultural management practices are among the major drivers of agricultural nitrogen (N) loss. Legislation and management incentives for measures to mitigate N loss should eventually be carried out at the individual farm level. Consequently, an appropriate scale to simulate N loss from a scientific perspective should be at the farm scale. A data set of more than 4000 agricultural fields with combinations of climate, soils and agricultural management which overall describes the variations found in the Baltic Sea drainage basin was constructed. The soil–vegetation–atmosphere model Daisy (Hansen et al. 2012) was used to simulate N loss from the root zone of all agricultural fields in the data set. From the data set of Daisy simulations, we identified the most important drivers for N loss by multiple regression statistics and developed a statistical N loss model. By applying this model to a basin-wide data set on climate, soils and agricultural management at a 10 × 10 km scale, we were able to calculate root-zone N losses from the entire Baltic Sea drainage basin and identify N loss hot spots in a consistent way and at a level of detail not hitherto seen for this area. Further, the root-zone N loss model was coupled to estimates of nitrogen retention in catchments separated into retention in groundwater and retention in surface waters allowing calculation of the coastal N loading.
Abstract
Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers andplant breeders in addressing the challenges of climate change by simulating alternative roads of adap-tation. They can also provide management decision support under current conditions. A drawback ofexisting grass models is that they do not take into account the effect of winter stresses, limiting theiruse for full-year simulations in areas where winter survival is a key factor for yield security. Here, wepresent a novel full-year PBM for grassland named BASGRA. It was developed by combining the LIN-GRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winterprocesses. We present the model and show how it was parameterized for timothy (Phleum pratense L.),the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRAsimulates the processes taking place in the sward during the transition from summer to winter, includ-ing growth cessation and gradual cold hardening, and functions for simulating plant injury due to lowtemperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data fromfive different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudesfrom 59◦to 70◦N) and soil conditions. The total dataset included 11 variables, notably above-ground drymatter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used inthe calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector fromthe single, Bayesian calibration, nearly all measured variables were simulated to an overall normalizedroot mean squared error (NRMSE) < 0.5. For many site × experiment combinations, NRMSE was <0.3. Thetemporal dynamics were captured well for most variables, as evaluated by comparing simulated timecourses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robustmodel, allowing for simulation of growth and several important underlying processes with acceptableaccuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be testedfurther using independent data from a wide range of growing conditions. Finally we show an exampleof application of the model, comparing overwintering risks in two climatically different sites, and dis-cuss future model applications. Further development work should include improved simulation of thedynamics of C reserves, and validation of winter tiller dynamics against independent data.
Abstract
No abstract has been registered
Authors
Yuka Kojima Aniko Varnai Takuya Ishida Naoki Sunagawa Dejan Petrovic Kiyohiko Igarashi Jody Jellison Barry Goodell Gry Alfredsen Bjørge Westereng Vincentius Gerardus Henricus Eijsink Makoto YoshidaAbstract
No abstract has been registered
Authors
Göran Ståhl Svetlana Saarela Sebastian Schnell Sören Holm Johannes Breidenbach Sean P. Healey Paul L. Patterson Steen Magnussen Erik Næsset Ronald E. McRoberts Timothy G. GregoireAbstract
No abstract has been registered
Authors
Csilla Farkas Sigrun Hjalmarsdottir Kværnø Alexander Melvold Engebretsen Robert Barneveld Johannes DeelstraAbstract
No abstract has been registered