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New (a)biotic conditions, resulting from climate change, are expected to change disturbance dynamics, e.g., wind throw, forest fires and insect outbreaks, and their interactions. Unprecedented natural disturbance 30 dynamics might alter the capability of forest ecosystems to buffer atmospheric CO2 increases in the atmosphere, even leading to the risk that forests transform from sinks into sources of CO2. This study aims to enhance the capability of the ORCHIDEE land surface model to study the impacts of climate change on bark beetle dynamics and subsequent effects on forest functioning. The bark beetle outbreak model is based on previous work by Temperli et al. 2013 for the LandClim landscape model. The new implementation of this model in ORCHIDEE r7791 35 accounts for the following differences between ORCHIDEE and LandClim: (1) the coarser spatial resolution of ORCHIDEE, (2) the higher temporal resolution of ORCHIDEE, and (3) the pre-existing process representation of wind throw, drought, and forest structure in ORCHIDEE. Qualitative evaluation demonstrated the model's ability to simulate a wide range of observed post-disturbance forest dynamics: (1) resistance to bark beetle infestation even in the presence of windthrow events; (2) slow transition (3-7 years) from an endemic into an epidemic bark beetle population following medium intensity window events at cold locations; and (3) fast transition (1-3 years) from endemic to epidemic triggered by strong windthrow events. Although all simulated sites eventually recovered from disturbances, the time needed to recover varied from 5 to 10 years depending on the disturbance dynamics. In addition to enhancing the functionality of the ORCHIDEE model, the new bark beetle model represents a fundamental change in the way mortality is simulated as it replaces a framework in which mortality is conceived as a continuous process by one in which mortality is represented by abrupt events. Changing the mortality framework provided new insights into carbon balance estimates, showing the risk of overestimating the short-term sequestration potential under the commonly used continuous mortality framework. [ABSTRACT FROM AUTHOR]

Studying how deadwood mitigates the rockfall hazard in mountain forests is key to understanding the influence of climate-induced disturbances on the protective capacity of mountain forests. Both experimental quantification and numerical process modeling are needed to address this question. Modeling provides detailed insights into the rock–deadwood interaction and can therefore be used to develop effective forest management strategies. Here, we introduce an automatic deadwood generator (ADG) for assessing the impact of fresh woody storm debris on the protective capacity of a forest stand against rockfall. The creation of various deadwood scenarios allows us to directly quantify the mitigation potential of deadwood. To demonstrate the functionality of the proposed ADG method, we compare deadwood log patterns, deadwood effective height, and mesoscale surface ruggedness observed in field surveys in a natural windthrow area with their simulated counterparts. Specifically, we consider two sites near Lake Klöntal, Switzerland, where a major windthrow event occurred in 2019. We perform rockfall simulations for the time (a) before, (b) directly after, and (c) 10 years after the windthrow event. We further compare the results with (d) a simulation with complete clearing of the thrown wood: in other words, a scenario with no standing forest remaining. We showcase an integration of deadwood into rockfall simulations with realistic deadwood configurations alongside a diameter at breast height (DBH)- and rot-fungi-dependent maximum deadwood breaking energy. Our results confirm the mitigation effect of deadwood, which significantly reduces the jump heights and velocities of 400 kg rocks. Our modeling results suggest that, even a decade after the windthrow event, deadwood has a stronger protective effect against rockfall than that provided by standing trees. We conclude that an ADG can contribute to the decision-making involved in forest and deadwood management after disturbances. [ABSTRACT FROM AUTHOR]

Severe winds are among the main causes of disturbances in boreal and temperate forests. Here, we present a new geographic information system (GIS) database of stand-replacing windthrow events in the forest zone of European Russia (ER) for the 1986–2017 period. The delineation of windthrow areas was based on the full Landsat archive and two Landsat-derived products on forest cover change, namely the Global Forest Change and the Eastern Europe's forest cover change datasets. Subsequent verification and analysis of each windthrow was carried out manually to determine the type of related storm event, its date or date range, and geometrical characteristics. The database contains 102 747 elementary areas of damaged forest that were combined into 700 windthrow events caused by 486 convective or non-convective storms. The database includes stand-replacing windthrows only with an area > 0.05 and > 0.25 km 2 for the events caused by tornadoes and other storms, respectively. Additional information such as weather station reports and event descriptions from media sources is also provided. The total area of stand-replacing windthrows amounts to 2966 km 2 , which is 0.19 % of the forested area of the study region. Convective windstorms contribute 82.5 % to the total wind-damaged area, while tornadoes and non-convective windstorms are responsible for 12.9 % and 4.6 % of this area, respectively. Most of the windthrow events in ER happened in summer, which is in contrast to Western and Central Europe, where they mainly occur in autumn and winter. Due to several data and method limitations, the compiled database is spatially and temporally inhomogeneous and hence incomplete. Despite this incompleteness, the presented database provides a valuable source of spatial and temporal information on windthrow in ER and can be used by both science and management. The database is available at 10.6084/m9.figshare.12073278.v6 (Shikhov et al., 2020). [ABSTRACT FROM AUTHOR]

Windstorms are natural disturbance agents in forests playing a role in natural forest regeneration. In Finland, the most severe individual windstorms have commonly damaged 2–4 million m 3 of timber. In addition to financial losses caused to forest owners, windthrown trees have in many cases seriously disrupted the functionality of the national power grid. Communicating windstorm risks in duty forecasting is difficult. In this study, we aimed at developing windstorm impact estimates for forest damage in Finland to help the forecaster to improve communication of the risks of windstorms. We have compared the volume of forest damage caused by the most intense windstorms in Finland during the recent decade to the observed maximum inland wind gust speeds associated with the same windstorms. It was found out that the volume of forest damage follows approximately a power relation as a function of wind gust speed with a power of ∼10. This is a tentative estimate because of a short time series and small number of inspected windstorms. Moreover, also wind direction, location of the affected area and soil properties among other factors have an impact to the amount of damage as illustrated in our inspection. Despite the shortness of the time series, we believe that our results demonstrating the steep increase in the impacts of windstorms with an increasing windstorm intensity are valuable. However, more detailed investigations with longer time series are needed in order to more specifically communicate the windstorm risks and their impacts in boreal forests. [ABSTRACT FROM AUTHOR]

Carbon and water dynamics of disturbed forest sites differ significantly from the mature stand. Stand-replacing phenomena as windthrow do not only alter forests' ability to sequester carbon but also affects water vapor exchange with the atmosphere due to the great reduction of evapotranspiration. The choice of reforestation technique at these vulnerable post-windthrow sites turns out to be crucial regarding not only net CO2 emissions changes in time but also the young plantation resistance to the water stress conditions. In this study we have compared results of already 6 years of continuous, real-time measurements at two windthrow forest sites in Trzebciny Forest District in northwest Poland. The main objective of this study was to determine how two completely different reforestation techniques in windthrow areas impact net ecosystem production (NEP) of this Scots pine forest ecosystem under similar meteorological and soil conditions. These two techniques were: conventional (Tlen I site- uprooted stumps pulled out and removed from the site followed by ploughing), and non-conventional (Tlen II site- all stumps left on the site to decompose with no ploughing). At both sites we measured carbon dioxide (CO2) and water (H2O) fluxes using the eddy covariance (EC) technique. Our results indicate that both sites became significant carbon (C) sources after the windthrow (up to 575 56 g C m-2 y-1 in the first year, Tlen I). However, the Tlen I (conventional technique) lost over 30% less C than Tlen II during the 2015-2016 observation period. In the next two years (2017-2018) the decrease in net C emission was several times greater at Tlen I than at Tlen II. Moreover, the annual net ecosystem production (NEP) at conventionally reforested windthrow site reached C neutrality (NEP = 0) six years after windthrow, while the non-conventionally managed area was still a significant C source. So far then, the currently widely applied conventional reforestation technique in wind-disturbed Polish forest appeared to be more effective in decreasing C losses than a technique that leaves stumps to decompose and avoids ploughing. During the study period there were two relatively wet years (2016 and 2017) which allowed both Scots pine plantations to grow and develop very well. Although, the occurrence of summer drought in 2015 affected the non-conventionally reforested treatment, while at the site which had been ploughed, there was no sign of water stress. It comes from the fact that furrows, where organic matter lays upside-down on the previous soil cover, served well as a retention agent, supplying young trees with water at the times of its shortage. Similar effect was visible also in spring 2018. The results from both study areas were also compared with CO2 and H2O fluxes from the mature pine stand (Tuczno site) - the closest analogue to the pre-storm stands from the Tlen I and Tlen II sites. Presented studied gives an insight into the carbon and water dynamics at differently managed wind-disturbed forest sites, stressing out the differences in coping with water stress. [ABSTRACT FROM AUTHOR]

Protection forests effectively preserve people and infrastructures against natural hazardssuch as rockfall, snow avalanches, landslides, debris flows, soil erosion and floods.Consequently, a reduction of this protective effect due to changes in forest structurecan drastically increase the degree of risk related to these phenomena. The Vaiawinter storm (29-30 October 2018) affected 41000 ha of forest in North-EasternItaly, with an amount of windthrow timber volume of 8.6•106 m3, compromisingthe protective function of a large portion of the forests. The aim of this study is toevaluate changes in the protective effect against rockfall of a forest located on thesouthern slope of the Mt. Pore after the damages of the Vaia winter storm. Threescenarios have been considered: 1) forest before the windstorm (condition at summer2018), 2) uncleared windthrow (current status after the windstorm), and 3) clearedwindthrow (removal of all fallen dead stems). Rockfall numerical simulations have beenpursued considering these three scenarios using the 3D rockfall trajectory modelRockyfor3D. The protective effect of the forest in the three scenarios has been evaluatedusing the model outputs to calculate quantitative indicators at the distance of theinfrastructures at risk. Field surveys and a UAV survey carried out during summer 2018allowed the collection and the spatialization of the model input parameters, includingthe forest characteristics before the wind storm. Furthermore, after event on-siteinvestigations allowed the estimation of the windthrow damages and the calibration ofthe model parameters in the second and third scenarios. Modelling results showthat the great amount of dead stems lying on the ground after windthrow (secondscenario) can provide protection against rockfall comparable to the living forest (firstscenario) in the short period. Effectively, even though the forest and the elements onthe ground are not able to stop all the boulders, they can significantly decreasethe kinetic energy of the boulders, reducing the speed and rebound height, anddecreasing the magnitude of the phenomenon. On the other hand, clearing the windthrow(scenario 3) increase the rockfall risk, especially for the infrastructures at higherdistances from the rock cliff. Finally, field surveys supported by remote sensingsurveys are revealed essential in order to achieve simulations adherent to reality. [ABSTRACT FROM AUTHOR]

Wind is the most prominent abiotic damage element for Finnish forests. Moreover, there isevidence that the amount of wind damage is increasing over much of continental Europe.Hence, effective tools are required to estimate current spatial patterns of wind risk overlarge forested areas and possible changes in risk patterns for planned silviculturaloperations. We present a method for generating maps of forest risk to wind damage byusing ALS data along with a modified version of the HWIND model (Heinonenet al 2009). ALS-derived stand height, stand geometry and intra-stand gap data(e.g., caused by clearcuts) was provided to the wind damage model, along with theprevalent wind direction. The output was spatially explicit critical wind speeds neededto uproot trees, for various (gridded) points in the forest stands. Further, a windmultiplier field generated from high resolution digital elevation data and foreststand data was used to better identify points where this critical wind speed could beexceeded (for example, due to local topographic effects). We tested the efficacy of ourapproach using more than 70 field points from the field where various wind-damagedtrees was recorded. We used an appropriate model tailored to the 'presence-only’dataset for this particular analysis. Our work highlights the importance of consideringwind damage risk effects for spatial optimization of forest operations planning. [ABSTRACT FROM AUTHOR]

The uncertainty about future changes in forest disturbance regimes has highlighted the need to consider disturbances in forest management. In order to effectively reduce the vulnerability of forests to disturbances, detailed information about the risks is needed to support management decisions.Here, our aim is to provide such information by creating high-resolution maps of forest wind and snow damage probability for Finland. First, damage probability models separately for wind and snow were developed based on damage observations in the Finnish national forest inventory (NFI). Three different statistical and machine learning methods were used and compared for the damage probability models – generalized linear models (GLM), generalized additive models (GAM) and boosted regression trees (BRT). Then, the damage probability maps were created in 16 m x 16 m grid resolution by combining the damage models with national coverage spatial data about the model predictors (forest properties, management history, soil properties and climatic conditions) compiled from different sources. Finally, we test the predictive performance of the maps with a large test data from new NFI damage observations not included in model fitting, demonstrating the ability of the maps to identify forests vulnerable to wind and snow disturbances.The maps provide a tool for identifying the vulnerable forest areas and communicating disturbance risks to forest owners and managers. Therefore, they have potential to steer forest management practices to a more disturbance-aware direction by providing easily available high-resolution information about damage probabilities to support management decisions. [ABSTRACT FROM AUTHOR]