Abstract. Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases of wind-related impact at a pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND is comprised of more than 80 000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018 and describes them in a harmonized and consistent geographical vector format. The database includes all major windstorms that occurred over the observational period (e.g. Gudrun, Kyrill, Klaus, Xynthia and Vaia) and represents approximately 30 % of the reported damaging wind events in Europe. Correlation analyses between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p value < 0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. The potential of FORWIND is explored for a range of challenging topics and scientific fields, including scaling relations of wind damage, forest vulnerability modelling, remote sensing monitoring of forest disturbance, representation of uprooting and breakage of trees in large-scale land surface models, and hydrogeological risks following wind damage. Overall, FORWIND represents an essential and open-access spatial source that can be used to improve the understanding, detection and prediction of wind disturbances and the consequent impacts on forest ecosystems and the land–atmosphere system. Data sharing is encouraged in order to continuously update and improve FORWIND. The dataset is available at https://doi.org/10.6084/m9.figshare.9555008 (Forzieri et al., 2019).

In forested watersheds, large woody debris (LWD) is an integral component of river channels and floodplains. Fallen trees have a significant impact on physical and ecological processes in fluvial ecosystems. An enormous body of literature concerning LWD in river corridors is currently available. However, synthesis and statistical treatment of the published data are hampered by the heterogeneity of methodological approaches. Likewise, the precision and accuracy of data arising out of published surveys have yet to be assessed. For this review, a literature scrutiny of 100 randomly selected research papers was made to examine the most frequently surveyed LWD variables and field procedures. Some 29 variables arose for individual LWD pieces, and 15 variables for wood accumulations. The literature survey revealed a large variability in field procedures for LWD surveys. In many studies (32), description of field procedure proved less than adequate, rendering the results impossible to reproduce in comparable fashion by other researchers. This contribution identifies the main methodological problems and sources of error associated with the mapping and measurement of the most frequently surveyed variables of LWD, both as individual pieces and in accumulations. The discussion stems from our own field experience with LWD survey in river systems of various geomorphic styles and types of riparian vegetation in the Czech Republic in the 2004-10 period. We modelled variability in terms of LWD number, volume, and biomass for three geomorphologically contrasting river systems. The results appeared to be sensitive, in the main, to sampling strategy and prevailing field conditions; less variability was produced by errors of measurement. Finally, we propose a comprehensive standard field procedure for LWD surveyors, including a total of 20 variables describing spatial position, structural characteristics and the functions and dynamics of LWD. However, resources are only rarely available for highly time-demanding surveys. We therefore include a set of core LWD metrics for routine baseline surveys of individual LWD pieces (diameter, length, rootwad size, preservation of branches and rootwad, geomorphological/ecological function, stability/mobility) and wood accumulations (number of LWD pieces, geometrical dimensions, channel blockage, wood/air ratio), which may provide useful background information for river management, hydromorphological assessment, habitat evaluation, and inter-regional comparisons.

Abstract. Strong winds may uproot and break trees and represent one of the major natural disturbances for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the climate change effects. Despite the importance of such natural disturbances, there are currently no spatially-explicit databases of wind-related impact at Pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND comprises more than 80,000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018, and describes them in a harmonized and consistent geographical vector format. Correlation analyses performed between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p-value<0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. Overall, FORWIND represents a valuable and open-access spatial source to improve our understanding of the vulnerability of forests to winds and develop large-scale monitoring/modelling of natural disturbances. Data sharing is encouraged in order to continuously update and improve FORWIND. The dataset is available at https://doi.org/10.6084/m9.figshare.9555008 (Forzieri et al., 2019).

This study examined the large wood (LW) load and transport during the non-flood period (2009-2018) following major floods that occurred in 2002 and 2006 within the inter-dam reach of the Dyje River (Czech-Austrian border). The LW load was examined in 36 river corridor segments scattered within the reach in the 2009-2018 period. Two whole-reach surveys (2011 and 2019) on LW frequency and distribution were conducted, and the export of LW to the downstream reservoir was analysed between June 2013 and December 2018. In the period of non-flood discharges, the recruitment and depletion of LW were highly variable processes in space and time, leading to a considerable change in the total LW quantity. Whereas the total number of LW pieces decreased, the total LW volume increased because of the increasing dimensions of newly recruited pieces. The annual variability in the quantity of newly recruited pieces was better explained by the variation in the maximum annual discharges (y = 41.043ln(x) + 3.2737, R 2 = 0.5352) than by the variability in the number of days with wind gusts >17.2m/s (y = 1.5004x + 82.096, R 2 = 0.118). The land use change with the abandonment of human settlements after World War II and the progressive expansion of forest was the major historical factor driving the increased recruitment of LW to the river corridor. While the 2006 (>100-year RI) flood brought approximately 1,250 LW pieces to the reservoir, the 2013 (1.5-year RI) flood delivered 45 pieces. The long-term average monthly input of LW to the reservoir was 7.7 pieces. The exceptional low-magnitude flood of 2013, which occurred at the beginning of the monitoring period, was shown to be a threshold above which the number of LW pieces that floated to the dam significantly increased.

Abstract:Norway spruce dominates mountain forests in Europe. Natural variations in the mountainous coniferous forests are strongly influenced by all the main components of forest and landscape dynamics: species diversity, the structure of forest stands, nutrient cycling, carbon storage, and other ecosystem services. This paper deals with an empirical windthrow risk model based on the integration of logistic regression into GIS to assess forest vulnerability to wind-disturbance in the mountain spruce forests of Šumava National Park (Czech Republic). It is an area where forest management has been the focus of international discussions by conservationists, forest managers, and stakeholders. The authors developed the empirical windthrow risk model, which involves designing an optimized data structure containing dependent and independent variables entering logistic regression. The results from the model, visualized in the form of map outputs, outline the probability of risk to forest stands from wind in the examined territory of the national park. Such an application of the empirical windthrow risk model could be used as a decision support tool for the mountain spruce forests in a study area. Future development of these models could be useful for other protected European mountain forests dominated by Norway spruce.