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.
2023
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Purpose of Review Forestry in northern temperate and boreal regions relies heavily on conifers. Rapid climate change and associated increases in adverse growing conditions predispose conifers to pathogens and pests. The much longer generation time and presumably, therefore, lower adaptive capacity of conifers relative to their native or non-native biotic stressors may have devastating consequences. We provide an updated overview of conifer defences underlying pathogen and pest resistance and discuss how defence traits can be used in tree breeding and forest management to improve resistance. Recent Findings Breeding of more resilient and stress-resistant trees will benefit from new genomic tools, such as genotyping arrays with increased genomic coverage, which will aid in genomic and relationship-based selection strategies. However, to successfully increase the resilience of conifer forests, improved genetic materials from breeding programs must be combined with more flexible and site-specific adaptive forest management. Summary Successful breeding programs to improve conifer resistance to pathogens and pests provide hope as well as valuable lessons: with a coordinated and sustained effort, increased resistance can be achieved. However, mechanisms underlying resistance against one stressor, even if involving many genes, may not provide any protection against other sympatric stressors. To maintain the adaptive capacity of conifer forests, it is important to keep high genetic diversity in the tree breeding programs. Choosing forest management options that include diversification of tree-species and forest structure and are coupled with the use of genetically improved plants and assisted migration is a proactive measure to increase forest resistance and resilience to foreseen and unanticipated biotic stressors in a changing climate.
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2022
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Authors
Marta Vergarechea Rasmus Astrup Carolin Fischer Knut Øistad Clemens Blattert Markus Hartikainen Kyle Eyvindson Fulvio Di Fulvio Nicklas Forsell Daniel Burgas Astor Toraño-Caicoya Mikko Mönkkönen Clara Antón FernándezAbstract
To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving mitigation targets and at the same time meet nationally determined targets for other FES. Using data from the Norwegian national forest inventory (NFI) we simulated the development of Norwegian forests under different management regimes and defined different forest policy scenarios, according to the most relevant forest policies in Norway: national forest policy (NFS), biodiversity policy (BIOS), and bioeconomy policy (BIES). Finally, through multi-objective optimization, we identified the combination of management regimes matching best with each policy scenario. The results for all scenarios indicated that Norway will be able to satisfy wood demands of up to 17 million m3 in 2093. However, the policy objectives for FES under each scenario caused substantial differences in terms of the management regimes selected. We observed that BIES and NFS resulted in very similar forest management programs in Norway, with a dominance of extensive management regimes. In BIOS there was an increase of set aside areas and continuous cover forestry, which made it more compatible with biodiversity indicators. We also found multiple synergies and trade-offs between the FES, likely influenced by the definition of the policy targets at the national scale.
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Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment.
Abstract
Stand-level growth and yield models are important tools that support forest managers and policymakers. We used recent data from the Norwegian National Forest Inventory to develop stand-level models, with components for dominant height, survival (number of survived trees), ingrowth (number of recruited trees), basal area, and total volume, that can predict long-term stand dynamics (i.e. 150 years) for the main species in Norway, namely Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pubescens Ehrh. and Betula pendula Roth). The data used represent the structurally heterogeneous forests found throughout Norway with a wide range of ages, tree size mixtures, and management intensities. This represents an important alternative to the use of dedicated and closely monitored long-term experiments established in single species even-aged forests for the purpose of building these stand-level models. Model examination by means of various fit statistics indicated that the models were unbiased, performed well within the data range and extrapolated to biologically plausible patterns. The proposed models have great potential to form the foundation for more sophisticated models, in which the influence of other factors such as natural disturbances, stand structure including species mixtures, and management practices can be included.
Authors
Johannes Schumacher Håvard Toft Larsen Paul McLean Marius Hauglin Rasmus Astrup Johannes BreidenbachAbstract
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%.