A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and birch (Betula spp.) is presented. The model predicts the critical turning moment and wind speed at which the trees will be uprooted or break at forest margins. The resistance to uprooting is predicted using the estimate of the root-soil plate weight to derive a resistive moment, while the resistance to stem breakage relies on values for the modulus of rupture determined for different species of timber. A tree is assumed to be uprooted if the total turning moment exceeds the support provided by the root-soil plate anchorage. Similarly, a tree is assumed to break if the breaking stress acting on the stem exceeds a critical value of the modulus of rupture. The model is in general quite sensitive to parameter changes, which partly results from the location in the forest to which it was designed to apply (the stand edge). The predictions of the critical turning moments needed to uproot and break trees nevertheless give a good agreement on average with the Finnish tree-pulling data for Scots pine, Norway spruce, and birch.

This study investigated the sensitivity of managed boreal forests to climate change, with consequent needs to adapt the management to climate change. Model simulations representing the Finnish territory between 60 and 70° N showed that climate change may substantially change the dynamics of managed boreal forests in northern Europe. This is especially probable at the northern and southern edges of this forest zone. In the north, forest growth may increase, but the special features of northern forests may be diminished. In the south, climate change may create a suboptimal environment for Norway spruce. Dominance of Scots pine may increase on less fertile sites currently occupied by Norway spruce. Birches may compete with Scots pine even in these sites and the dominance of birches may increase. These changes may reduce the total forest growth locally but, over the whole of Finland, total forest growth may increase by 44%, with an increase of 82% in the potential cutting drain. The choice of appropriate species and reduced rotation length may sustain the productivity of forest land under climate change.

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Wind affects the structure and functioning of a forest ecosystem continuously and may cause significant economic loss in managed forests by reducing the yield of recoverable timber, increasing the cost of unscheduled thinning and clear-cuttings, and creating problems in forestry planning. Furthermore, broken and uprooted trees within the forest are subject to insect attack and may provide a suitable breeding substrate, endangering the remaining trees. Therefore, an improved understanding of the processes behind the occurrence of wind-induced damage is of interest to many forest ecologists, but may also help managers of forest resources to make appropriate management decisions related to risk management. Using fundamental physics, empirical experiments, and mechanistic model-based approaches in interaction, we can study the susceptibility of tree stands to wind damage as affected by the wind and site and tree/stand characteristics and management. Such studies are not possible based on statistical approaches alone, which are not able to define the causal links between tree parameters and susceptibility to wind damage. The aim of this paper is to review the recent work done related to tree-pulling and wind tunnel experiments and mechanistic modeling approaches to increase our understanding of the mechanical stability of trees under static loading.

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

Reliable models are required to assess the impacts of climate change on forest ecosystems. Precise and independent data are essential to assess this accuracy. The flux measurements collected by the EUROFLUX project over a wide range of forest types and climatic regions in Europe allow a critical testing of the process‐based models which were developed in the LTEEF project. The ECOCRAFT project complements this with a wealth of independent plant physiological measurements. Thus, it was aimed in this study to test six process‐based forest growth models against the flux measurements of six European forest types, taking advantage of a large database with plant physiological parameters. The reliability of both the flux data and parameter values itself was not under discussion in this study. The data provided by the researchers of the EUROFLUX sites, possibly with local corrections, were used with a minor gap‐filling procedure to avoid the loss of many days with observations. The model performance is discussed based on their accuracy, generality and realism. Accuracy was evaluated based on the goodness‐of‐fit with observed values of daily net ecosystem exchange, gross primary production and ecosystem respiration (gC m−2 d−1), and transpiration (kg H2O m−2 d−1). Moreover, accuracy was also evaluated based on systematic and unsystematic errors. Generality was characterized by the applicability of the models to different European forest ecosystems. Reality was evaluated by comparing the modelled and observed responses of gross primary production, ecosystem respiration to radiation and temperature. The results indicated that: Accuracy. All models showed similar high correlation with the measured carbon flux data, and also low systematic and unsystematic prediction errors at one or more sites of flux measurements. The results were similar in the case of several models when the water fluxes were considered. Most models fulfilled the criteria of sufficient accuracy for the ability to predict the carbon and water exchange between forests and the atmosphere. Generality. Three models of six could be applied for both deciduous and coniferous forests. Furthermore, four models were applied both for boreal and temperate conditions. However, no severe water‐limited conditions were encountered, and no year‐to‐year variability could be tested. Realism. Most models fulfil the criterion of realism that the relationships between the modelled phenomena (carbon and water exchange) and environment are described causally. Again several of the models were able to reproduce the responses of measurable variables such as gross primary production (GPP), ecosystem respiration and transpiration to environmental driving factors such as radiation and temperature. Stomatal conductance appears to be the most critical process causing differences in predicted fluxes of carbon and water between those models that accurately describe the annual totals of GPP, ecosystem respiration and transpiration. As a conclusion, several process‐based models a...