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.
2019
Abstract
No abstract has been registered
Abstract
Despite sophisticated mathematical models, the theory of microevolution is mostly treated as a qualitative rather than a quantitative tool. Numerical measures of selection, constraints, and evolutionary potential are often too loosely connected to theory to provide operational predictions of the response to selection. In this paper, we study the ability of a set of operational measures of evolvability and constraint to predict short‐term selection responses generated by individual‐based simulations. We focus on the effects of selective constraints under which the response in one trait is impeded by stabilizing selection on other traits. The conditional evolvability is a measure of evolutionary potential explicitly developed for this situation. We show that the conditional evolvability successfully predicts rates of evolution in an equilibrium situation, and further that these equilibria are reached with characteristic times that are inversely proportional to the fitness load generated by the constraining characters. Overall, we find that evolvabilities and conditional evolvabilities bracket responses to selection, and that they together can be used to quantify evolutionary potential on time scales where the G‐matrix remains relatively constant.
Abstract
No abstract has been registered
Abstract
Surface mould growth contributes to the colour changes of outdoor exposed wood over time. Modelling mould growth can thus help visualize wooden facades’ colour development, which can improve facade design and service life. However, existing wood mould models do not consider transient wetting effects that occur outdoors due to precipitation and condensation. To address this, four mould models were evaluated using laboratory experimental data that included exposure to transient wetting. First, the models (the original and the updated VTT model, the biohygrothermal model and the mould resistance design (MRD) model) were evaluated for Scots pine sapwood. For this evaluation, the transient wetting effect was implemented in the models by using hourly wood surface relative humidity (RH), calculated from electrical resistance measurements, as input. This showed that the original and the updated VTT model gave best fit to the experimental data. However, further evaluation of these two models for more wood materials showed that the updated VTT model was sensitive to the choice of material parameters. Large discrepancies occurred when varying the material parameters in the updated VTT model. Finally, different estimates of RH were tested in the original VTT model. Using wood surface RH as input gave best fit to the experimental data, and ambient air RH gave poorest fit. Overall, the results indicate that the original VTT model is fairly reliable and can be used to predict mould growth on wooden claddings exposed to transient wetting as long as the wood surface climate is used as climatic input data.
Authors
Jamal Zaherpour Nick Mount Simon N. Gosling Rutger Dankers Stephanie Eisner Dieter Gerten Xingcai Liu Yoshimitsu Masaki Hannes Müller Schmied Qiuhong Tang Yoshihide WadaAbstract
This study presents a novel application of machine learning to deliver optimised, multi-model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify the approach using runoff simulations from five GHMs across 40 large global catchments. The benchmarked, median performance gain of the MMC solutions is 45% compared to the best performing GHM and exceeds 100% when compared to the ensemble mean (EM). The performance gain offered by MMC suggests that future multi-model applications consider reporting MMCs, alongside the EM and intermodal range, to provide end-users of GHM ensembles with a better contextualised estimate of runoff. Importantly, the study highlights the difficulty of interpreting complex, non-linear MMC solutions in physical terms. This indicates that a pragmatic approach to future MMC studies based on machine learning methods is required, in which the allowable solution complexity is carefully constrained.
Abstract
With climate change, the effect of global warming on snow cover is expected to cause range expansion and enhance habitat suitability for species at their northern distribution limits. However, how this depends on landscape topography and sex in size-dimorphic species remains uncertain, and is further complicated for migratory animals following climate-driven seasonal resource fluctuations across vast landscapes. Using 11 years of data from a partially migratory ungulate at their northern distribution ranges, the red deer (Cervus elaphus), we predicted sex-specific summer and winter habitat suitability in diverse landscapes under medium and severe global warming. We found large increases in future winter habitat suitability, resulting in expansion of winter ranges as currently unsuitable habitat became suitable. Even moderate warming decreased snow cover substantially, with no suitability difference between warming scenarios. Winter ranges will hence not expand linearly with warming, even for species at their northern distribution limits. Although less pronounced than in winter, summer ranges also expanded and more so under severe warming. Summer habitat suitability was positively correlated with landscape topography and ranges expanded more for females than males. Our study highlights the complexity of predicting future habitat suitability for conservation and management of size-dimorphic, migratory species under global warming.
Abstract
Knowledge about spatiotemporal variability of climate change effect on tree-ring width (TRW) and crown condition is essential to optimize the modelling of future forest ecosystem responses to the changing climate. Geographical differences in the climate–growth relationship are a reflection of the regional climatic conditions mainly. In this study, 175 Picea abies trees from the north-western edge of its geographical distribution in Central Norway were evaluated with respect to geographical and age-dependent differences during the common period of 1950–2015. The results showed that the most significant positive correlations between TRW and the current June temperature were unstable although the temperature increased. The correlations suddenly started to decrease (regardless of the site placement and tree age) at the beginning of the 1990s, but subsequently unexpectedly increased in the 2010s. The superposed epoch analysis revealed longer TRW regeneration of the southern plots (except over-mature trees) after negative pointer years compared to the northern plots. Previous summer temperature and related physiological processes (cone crops, storage of nutrients, etc.) significantly negatively affected P. abies growth in the current year. Additionally, our results showed that the selection of the chronology version (standard or residual) significantly affects the resulting correlations and thus must be carefully considered in dendroclimatological studies. Our main outputs can contribute to better understanding of the climate–growth relationship variability and general prediction of the radial growth.
Abstract
A novel method for age-independent site index estimation is demonstrated using repeated single-tree airborne laser scanning (ALS) data. A spruce-dominated study area of 114 km2 in southern Norway was covered by single-tree ALS twice, i.e. in 2008 and 2014. We identified top height trees wall-to-wall, and for each of them we derived based on the two heights and the 6-year period length. We reconstructed past, annual height growth in a field campaign on 31 sample trees, and this showed good correspondence with ALS based heights. We found a considerable increase in site index, i.e. about 5 m in the H40 system, from the old site index values. This increase corresponded to a productivity increase of 62%. This increase appeared to mainly represent a real temporal trend caused by changing growing conditions. In addition, the increase could partly result from underestimation in old site index values. The method has the advantages of not requiring tree-age data, of representing current growing conditions, and as well that it is a cost-effective method with wall-towall coverage. In slow-growing forests and short time periods, the method is least reliable due to possible systematic differences in canopy penetration between repeated ALS scans.
Abstract
No abstract has been registered
Authors
Olav Aaseth Hegnar Barry Goodell Claus Felby Lars Johansson Nicolé Labbe Keonhee Kim Vincent Eijsink Gry Alfredsen Aniko VarnaiAbstract
The recalcitrance bottleneck of lignocellulosic materials presents a major challenge for biorefineries, including second-generation biofuel production. Because of their abundance in the northern hemisphere, softwoods, such as Norway spruce, are of major interest as a potential feedstock for biorefineries. In nature, softwoods are primarily degraded by basidiomycetous fungi causing brown rot. These fungi employ a non-enzymatic oxidative system to depolymerize wood cell wall components prior to depolymerization by a limited set of hydrolytic and oxidative enzymes. Here, it is shown that Norway spruce pretreated with two species of brown-rot fungi yielded more than 250% increase in glucose release when treated with a commercial enzyme cocktail and that there is a good correlation between mass loss and the degree of digestibility. A series of experiments was performed aimed at mimicking the brown-rot pretreatment, using a modified version of the Fenton reaction. A small increase in digestibility after pretreatment was shown where the aim was to generate reactive oxygen species within the wood cell wall matrix. Further experiments were performed to assess the possibility of performing pretreatment and saccharification in a single system, and the results indicated the need for a complete separation of oxidative pretreatment and saccharification. A more severe pretreatment was also completed, which interestingly did not yield a more digestible material. It was concluded that a biomimicking approach to pretreatment of softwoods using brown-rot fungal mechanisms is possible, but that there are additional factors of the system that need to be known and optimized before serious advances can be made to compete with already existing pretreatment methods.