Mapping the probability of forest snow disturbances in Finland

The changing forest disturbance regimes emphasize the need for improved damage risk information. Here, our aim was to (1) improve the current understanding of snow damage risks by assessing the importance of abiotic factors, particularly the modelled snow load on trees, versus forest properties in predicting the probability of snow damage, (2) produce a snow damage probability map for Finland. We also compared the results for winters with typical snow load conditions and a winter with exceptionally heavy snow loads. To do this, we used damage observations from the Finnish national forest inventory (NFI) to create a statistical snow damage occurrence model, spatial data layers from different sources to use the model to predict the damage probability for the whole country in 16 x 16 m resolution. Snow damage reports from forest owners were used for testing the final map. Our results showed that best results were obtained when both abiotic and forest variables were included in the model. However, in the case of the high snow load winter, the model with only abiotic predictors performed nearly as well as the full model and the ability of the models to identify the snow damaged stands was higher than in other years. The results showed patterns of forest adaptation to high snow loads, as spruce stands in the north were less susceptible to damage than in southern areas and long-term snow load reduced the damage probability. The model and the derived wall-to-wall map were able to discriminate damage from no-damage cases on a good level (AUC > 0.7). The damage probability mapping approach identifies the drivers of snow disturbances across forest landscapes and can be used to spatially estimate the current and future disturbance probabilities in forests, informing practical forestry and decision-making and supporting the adaptation to the changing disturbance regimes.

Assessing the impacts of cell wall composition on the optimum stage for “Uradome” in moso bamboo

Snow damage is problematic when cultivating bamboo shoots, and “Uradome”, the practice of removing the tips of new shoots, is used as a preventative measure. Producers perform “Uradome” at empirical times, but there is no scientific basis for this. We hypothesized that differences in the structure and composition of the cell wall might affect the optimal timing of "Uradome" and analyzed the cell wall components of the “Uradome” portion. The lower plant sections broken by the “Uradome” had larger cellulose and lignin depositions than the upper sections. However, there were no differences in the lignin structure or ratio between the upper and lower nodes of the broken sections. This suggests that differences in the degree of cellulose and lignin deposition have significant effects on “Uradome” sites, and that the timing coincides with the development of one or two juvenile branches, which growers empirically consider to be the appropriate time. These results are considered to be new findings that scientifically support the cultivation management of bamboo that has been conducted empirically.

Sää- ja ilmastotiedot sekä uudet palvelut auttavat metsäbiotaloutta sopeutumaan ilmastonmuutokseen

Climate change will increase weather induced risks to forests, and thus effective adaptation measures are needed. In Säätyö project funded by the Ministry of Agriculture and Forestry, we have summarized the data that facilitate adaptation measures, developed weather and climate services that benefit forestry, and mapped what kind of new weather and climate services are needed in forestry. In addition, we have recorded key further development needs to promote adaptation. The Säätyö project developed a service product describing the harvesting conditions of trees based on the soil moisture assessment. The output includes an analysis of the current situation and a 10-day forecast. In the project we also tested the usefulness of long forecasts beyond three months. The weather forecasting service is sidelined and supplemented by another co-operation project between the Finnish Meteorological Institute and Metsäteho called HarvesterSeasons (https://harvesterseasons.com/). The HarvesterSeasons service utilizes long-term forecasts of up to 6 months to assess terrain bearing conditions. A test version of a wind damage risk tool was developed in cooperation with the Department of Forest Sciences of the University of Eastern Finland and the Finnish Meteorological Institute. It can be used to calculate the wind speeds required in a forest area for wind damage (falling trees). It is currently only suitable for researcher use. In the Säätyö project the possibility of locating the most severe wind damage areas immediately after a storm was also tested. The method is based on the spatial interpolation of wind observations. The method was used to analyze storms that caused forest damages in the summer and fall of 2020. The produced maps were considered illustrative and useful to those responsible for compiling the situational picture. The accumulation of snow on tree branches, can be modeled using weather data such as rainfall, temperature, air humidity, and wind speed. In the Säätyö project, the snow damage risk assessment model was further developed in such a way that, in addition to the accumulated snow load amount, the characteristics of the stand and the variations in terrain height were also taken into account. According to the verification performed, the importance of abiotic factors increased under extreme snow load conditions (winter 2017-2018). In ordinary winters, the importance of biotic factors was emphasized. According to the comparison, the actual snow damage could be explained well with the tested model. In the interviews and workshop, the uses of information products, their benefits, the conditions for their introduction and development opportunities were mapped. According to the results, diverse uses and benefits of information products and services were seen. Information products would make it possible to develop proactive forest management, which would reduce the economic costs caused by wind and snow damages. A more up-to-date understanding of harvesting conditions, enabled by information products, would enhance the implementation of harvesting and harvesting operations and the management of timber stocks, as well as reduce terrain, trunk and root damage. According to the study, the introduction of information is particularly affected by the availability of timeliness. Although the interviewees were not currently willing to pay for the information products developed in the project, the interviews highlighted several suggestions for the development of information products, which could make it possible to commercialize them.

Mapping the probability of forest snow disturbances in Finland

The changing forest disturbance regimes emphasize the need for improved damage risk information. In this study, our aim was to improve the current understanding of snow damage risks by assessing the importance of abiotic factors, particularly the modelled snow load on tree crowns, versus forest properties in predicting the probability of snow damage, producing a snow damage probability map for Finland and test its performance, and comparing the results for winters with typical snow load conditions and a winter with exceptionally heavy snow loads. To do this, we used damage observations from the Finnish national forest inventory (NFI) to create a statistical snow damage occurrence model, spatial data layers from different sources to use the model to predict the damage probability for the whole country in 16 × 16 m resolution. Snow damage reports in forest use declarations were used for testing the final map. Our results showed that best results were obtained when both abiotic and forest variables were included in the model. However, in the case of the high snow load winter, the model with only abiotic predictors performed nearly as well as the full model. The statistical models were also able to identify the snow damage stands more accurately for the heavy snow load winter. The two tested statistical modelling methods. The snow damage model and the derived wall-to-wall probability map were able to discriminate between the damage and no-damage cases on a good level. The model and the damage probability mapping approach identifies the drivers of and susceptibility factors to snow damage across forest landscapes. Moreover, it can be used to estimate the concurrent and future snow damage risks in forests, which informs practical forestry and decision-making regarding climate change mitigation and adaptation of forestry.

Influence of Different Thinning Treatments on Stand Resistance to Snow and Wind in Loblolly Pine (Pinus taeda L.) Coastal Plantations of Northern Iran

Loblolly pine (Pinus taeda L.) is one of the main exotic conifer species that has been widely planted for the past fifty years for timber production in the coastal areas of northern Iran. Heavy snowfall and strong winds can cause much damage to these forests over a short time span of only a few years. This study was conducted to estimate snow and wind damage and analyze the role of stand thinning in their resistance to snow and wind. Amount and type of snow and wind damage were examined through systematic (80 m × 80 m) sample plots (each plot area of 625 m2) in nine different stands (2–10 plots in each stand) in terms of age, structure, and silviculture history in three replications for each stand in April and May 2020. Results showed that the amount of snow and wind damage had a wide range from 1.3% to 30.7%. Snow damage was more than three times that of wind. Snow and wind damage in the young stands were significantly more serious (p < 0.01) than in the middle-aged and old stands, and damage was significantly higher (p < 0.01) in the unthinned stands than in the thinned ones. Slenderness coefficient (Height/Diameter ratio, HD ratio) of trees resulted to be a good indicator in young and middle-aged stands, while crown form indices (relative crown length and relative crown width) were acceptable indicators in old stands for risk of snow and wind damage. Our results showed that the normal thinning (15% of basal area) decreased snow and wind damage in all the stands, while the heavy thinning (35% of basal area) reduced the snow damage, but it increased the wind one. It is possible to recommend high intensity thinning in young stands, normal thinning in middle-aged stands, and light thinning (15% of basal area) in old ones.

Historical Relationship between Snow Depth and Damaged Area in South Korea

&lt;p&gt;Recently, snow disasters have been increased in South Korea due to the unexpected heavy snow in a region where winter gives little snow. For instance, 10 people were dead by the collapsed roof due to the unusual heavy snow. Many local governments do not have enough snow removal equipment because of little snow in winter season. Therefore, it has been important to estimate the amount of snow damage to prepare heavy snow disaster. There are not many researches to estimate damage of snow disaster in South Korea. In this study, historical snow damage data from 1994~2018 recorded in National Disaster Report were used to predict the future snow disaster damage using a statistical equation. However, it was not easy to predict the amount of snow damage when the heavy snow is happened in the area where no snow during the winter in history. Therefore, the relationship between the snow depth and damaged area were analyzed using the historical damage data. Principal multiple regression method was applied to develop the snow damage estimation function using the damaged area. The developed model could be applied to plan the budget for the snow removal equipment or snow damage reduction.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgement&lt;/strong&gt;:&lt;/p&gt;&lt;p&gt;This work was supported by Korea Environment Industry &amp; Technology Institute (KEITI) through Intelligent Management Program for Urban Water Resources Project, funded by Korea Ministry of Environment(MOE) (2019002950002).&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Nitrogen Availability Decreases the Severity of Snow Storm Damage in a Temperate Forest

Storms are among the greatest natural disturbances in temperate forests, and increased nitrogen (N) availability is thought to increase storm damage. However, the extent to which N availability increases damage from snowfall is less clear. To test how N availability might affect the susceptibility of trees to snow damage in a temperate forest, we took advantage of an opportunistic storm and surveyed damage in fertilized and unfertilized stands, and across a native N availability gradient. In response to a severe, early season snow storm—a consequence of Superstorm Sandy—the percentages of both basal area and stems damaged were lower in a fertilized watershed than in an unfertilized watershed. Across the native N availability gradient, the percentage of basal area damaged by snow decreased with higher soil N. The effects of N availability on damage were also affected by tree species. Our results suggest that N availability decreases damage from snow storms, contrary to our hypotheses drawn from broader studies. Understanding the relation between storm damage and N availability is important, considering the global increase in N deposition, and since severe storms are likely to become more prevalent with climate change.

Simulating the effects of wind and snow damage on the optimal management of Norwegian spruce forests

Overlooking the risk of wind and snow damage in forest planning may lead to suboptimal management prescriptions. In this study, we analysed the optimal management of an even-aged, spruce-dominated stand in Norway under the risk of snow and wind damage. The management aim was to maximize discounted net revenues of timber production. We used a simulation-optimization system based on models for stand dynamics and damage, using either deterministic or stochastic approach to consider risk. The different approaches to simulating damage resulted in 41 optimization cases. The results show that considering risk leads to earlier cuttings, lower growing stock densities towards the end of the rotations and changes in the number and intensity of thinnings. The inclusion of stochastic damage provided a valid approach for considering the uncertainty associated with the risk of damage. Ignoring the effect of wind and snow damage in the calculations resulted in up to 25 per cent overestimation of the revenues. The results from this study will help to integrate the risk of natural disturbances into forestry decision-making, and provide a better understanding of the implications that snow and wind damage have on optimal forest management.