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.
2022
Abstract
SiTree is a flexible, cross-platform, open-source framework for individual-tree simulators intended to facilitate accurate and flexible analyses of forest growth and yield, or more generally forest dynamics simulations. SiTree provides generic functionality to build customized individual-tree simulators using additional user-written code. In the forestry literature there are a wide variety of individual models that describe the different parts of forest growth and dynamics and new models are continuously developed and published. The aim of SiTree is to provide a broad community of R-users within forestry with an easily adaptable individual-tree simulator framework and an easily accessible tool for testing and combining new and existing models describing parts of forest growth dynamics.
Abstract
Using decades of satellite observations, Finnish and Norwegian scientists calculated the warming effect caused by changes in the snow and ice cover of the Arctic and Antarctic regions.
Authors
Anne Catriona Mehlhoop Bram Van Moorter Christer Moe Rolandsen Dagmar Hagen Aksel Granhus Rune Eriksen Thor Harald Ringsby Erling Johan SolbergAbstract
Like large carnivores, hunters both kill and scare ungulates, and thus might indirectly affect plant performance through trophic cascades. In this study, we hypothesized that intensive hunting and enduring fear of humans have caused moose and other forest ungulates to partly avoid areas near human infrastructure (perceived hunting risk), with positive cascading effects on recruitment of trees. Using data from the Norwegian forest inventory, we found decreasing browsing pressure and increasing tree recruitment in areas close to roads and houses, where ungulates are more likely to encounter humans. However, although browsing and recruitment were negatively related, reduced browsing was only responsible for a small proportion of the higher tree recruitment near human infrastructure. We suggest that the apparently weak cascading effect occurs because the recorded browsing pressure only partly reflects the long-term browsing intensity close to humans. Accordingly, tree recruitment was also related to the density of small trees 5–10 years earlier, which was higher close to human infrastructure. Hence, if small tree density is a product of the browsing pressure in the past, the cascading effect is probably stronger than our estimates suggest. Reduced browsing near roads and houses is most in line with risk avoidance driven by fear of humans (behaviorally mediated), and not because of excessive hunting and local reduction in ungulate density (density mediated).
Abstract
Heat Field Deformation (HFD) is a widely used method to measure sap flow of trees based on empirical relationships between heat transfer within tree stems and the sap flow rates. As an alternative, the Linear Heat Balance (LHB) method implements the same instrumental configuration as HFD but calculates the sap flow rates using analytical equations that are derived from fundamental conduction-convection heat transfer theories. In this study, we systematically compared the sap flow calculated using the two methods based on data that were recorded using the same instrument. The measurements were conducted on four Norway spruce trees. We aimed to evaluate the discrepancies between the sap flow estimates from the two methods and determine the underlying causes. Diurnal and day-to-day patterns were consistent between the sap flow estimates from the two methods. However, the magnitudes of the estimated sap flow were different between them, where LHB resulted in much lower estimates in three trees and slightly higher estimates in one compared to HFD. We also observed larger discrepancies in negative (reversed flow) than in positive sap flow, where the LHB resulted in lower reversed flow than HFD. Consequently, the seasonal budget estimated by LHB can be as low as ∼20% of that estimated by HFD. The discrepancies can be mainly attributed to the low wood thermal conductivities for the studied trees that lead to substantial underestimations using the LHB method. In addition, the sap flow estimates were very sensitive to the value changes of the empirical parameters in the calculations and, thus, using a proper case-specific value is recommended, especially for the LHB method. Overall, we suggest that, despite the strong theoretical support, the correctness of LHB outputs depends largely on the tree individuals and should be carefully evaluated.
Abstract
As a way to estimate evapotranspiration (ET), Heat Field Deformation (HFD) is a widely used method to measure sap flow of trees based on empirical relationships between heat transfer within tree stems and the sap flow rates. As an alternative, the Linear Heat Balance (LHB) method implements the same instrumental configuration as HFD but calculates the sap flow rates using analytical equations that are derived from fundamental conduction-convection heat transfer equations.
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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%.
Authors
Joyce Machado Nunes Romeiro Tron Haakon Eid Clara Antón Fernández Annika Kangas Erik TrømborgAbstract
It is expected that European Boreal and Temperate forests will be greatly affected by climate change, causing natural disturbances to increase in frequency and severity. To detangle how, through forest management, we can make forests less vulnerable to the impact of natural disturbances, we need to include the risks of such disturbances in our decision-making tools. The present review investigates: i) how the most important forestry-related natural disturbances are linked to climate change, and ii) different modelling approaches that assess the risks of natural disturbances and their applicability for large-scale forest management planning. Global warming will decrease frozen soil periods, which increases root rot, snow, ice and wind damage, cascading into an increment of bark beetle damage. Central Europe will experience a decrease in precipitation and increase in temperature, which lowers tree defenses against bark beetles and increases root rot infestations. Ice and wet snow damages are expected to increase in Northern Boreal forests, and to reduce in Temperate and Southern Boreal forests. However, lack of snow cover may increase cases of frost-damaged seedlings. The increased temperatures and drought periods, together with a fuel increment from other disturbances, likely enhance wildfire risk, especially for Temperate forests. For the review of European modelling approaches, thirty-nine disturbance models were assessed and categorized according to their required input variables and to the models’ outputs. Probability models are usually common for all disturbance model approaches, however, models that predict disturbance effects seem to be scarce.