Snow Breakage Research Articles

Two unprecedented outbreaks of the European spruce bark beetle, Ips typographus L. (Col., Scolytinae) in Austria since 2015: Different causes and different impacts on forests

Abstract Austria has been facing two outbreaks of the European spruce bark beetle, Ips typographus L., in the last ten years. In this study, we compile data of damage caused by I. typographus L. as well as storm and snow breakage from 2002 to 2022 in two regions affected by these bark beetle outbreaks based on the Documentation of Forest Damaging Factors in Austria and analyze them in context of climatic factors. The first outbreak started in 2015 and affected Norway spruce forests at low elevation (< 600 m) in the north of Austria. Annual damage peaked in 2018 at 3.3 million m3 (representing 2.6% of total growing stock in the area). The second outbreak started in 2021 and affected mountainous spruce forests in the south of Austria. In this case extensive damage by storm in 2018 and snow breakage in the two following winters preceded the bark beetle outbreak. Annual damage by I. typographus L. reached 1.7 million m3 (2.4% of growing stock) in 2022. Most forests are located on steep mountain slopes and have important protective function against natural hazards. High temperatures allowed completion of two generations up to 1,400 m elevation. Linear regression models showed that damage by I. typographus L. was significantly affected by climatic water balance. This effect was stronger in the north than in the south. We discuss the different patterns of the outbreaks and challenges for bark beetle management in the context of climate change.

Predicting snow damage in conifer forests using a mechanistic snow damage model and high-resolution snow accumulation data

ABSTRACT Forest damage caused by heavy wet snow accumulation in the canopy is the second most important abiotic forest disturbance agent in Nordic conifer stands after wind. The extent and frequency of snow damage in the future climate in the Nordic region is a major uncertainty. Few mechanistic models of snow damage risk to trees exist that could support forest management scenario analysis and decision making. We propose a snow damage risk model consisting of a numerical weather prediction-based snow accumulation model for forest canopies and a mechanistic critical snow load model. Snow damage probability predictions were validated on snow breakage data from the winters of 2016 and 2018 covering 3.5 million individual trees in south-eastern Norway derived from pre- and post-damage aerial laser scanning campaigns. The proposed model demonstrated satisfactory damage and no-damage class separation with an AUC of 0.72 and 0.77 in Norway spruce and Scots pine, respectively, and an F1 score of 0.7 in conifers taller than 10 m that suffered moderate stem breakage. The model achieved a classification accuracy that is comparable to that of statistical models but is simpler and requires fewer inputs.

Shoulder Season

Shoulder Season

Automatic detection of snow breakage at single tree level using YOLOv5 applied to UAV imagery

The assessment of forest abiotic damages such as snow breakage is important to ensure compensation to forest owners. Currently, information on the extent of snow breakage is gathered through time-consuming and potentially biased field surveys. In such situations where field surveys are still common practice, unmanned aerial vehicles (UAVs) are increasingly being used to provide a more cost-efficient and objective methods to answer forest information needs. Further, the advent of sophisticated computer vision techniques such as convolutional neural networks (CNNs) offers new ways to analyze image data more efficiently and accurately. We proposed an object detection method to automatically identify trees and classify them according to the damage by snow based on a YOLO CNN architecture. UAV imagery collected across 89 study areas and over the course of the entire year were manually annotated into a total of >55 K single trees classified as healthy, damaged, or dead. The annotated trees, along with the corresponding UAV imagery were used to train a YOLOv5 object detection model. Furthermore, we tested the effect of seasonality, and varying atmospheric and lighting conditions on the model’s performance. Based on an independent test set of data we found that the general model including all of the data (i.e. any seasons, atmospheric conditions, and time of the day) outperformed all other tested scenarios (i.e. precision = 62 %; recall = 61 %). Furthermore, we found that despite the fact that the snow damaged trees represented a minority class (i.e. 16 % of the annotated trees), they were detected with the largest precision (76 %) and recall (78 %). Finally, the general model transferred well across the variation in seasons, atmospheric and illumination conditions, making it suitable for usage for any new UAV image acquisition.

Development of a Climate-Sensitive Matrix Growth Model for Larix gmelinii Mixed-Species Natural Forests and Its Application for Predicting Forest Dynamics under Different Climate Scenarios

Larix gmelinii natural forests, which are of great ecological and economic importance, are mainly distributed in northeast China. Sustainable management of these forests play a vital role in ecological security in northeast China, especially in the context of climate change. Forest growth models, which support forest management decision-making, are lacking for Larix gmelinii natural forests, hampering the prescription of forest management strategies. In this study, we produced a climate-sensitive, transition-matrix model (CM) for Larix gmelinii natural forests. For comparison, a variable transition model without including climate change effects (NCM) and a fixed-parameter model (FM) were also built. We examined the performance of the CM, NCM, and FM by conducting short- (5 years) and long-term (100 years) simulations. The results showed that for short-term prediction, no significant difference was observed among the three predictive models. However, the long-term prediction ability of the CM under the three different RCPs was superior to that of the FM and NCM. The number of trees and basal area were predicted to increase under climate change, which might result in natural disasters, such as snow break, windthrow, and forest fire. Silvicultural practices, such as reducing the intermediate thinning interval and the enrichment planting of slow-growing trees, should be implemented to mitigate the deleterious effects of climate change.

Snow damage in plantations of Austrian pine and Scots pine in the western part of the Republic of Srpska

The paper presents research related to the harmful effects of snowfall in Austrian pine and Scots pine plantations in the western part of the Republic of Srpska. The most common types of tree damage are snow break and snowfall. The harmful effect of snow is more present in Scots pine plantations and at lower altitudes. Also, the harmful effect of snow is reflected in the reduction of the vitality of damaged trees, which become suitable for the attack of other harmful biotic factors, primarily harmful insects and fungi.

The influence of abiotic and biotic disturbances on the protective effect of alpine forests against avalanches and rockfalls

Abiotic and biotic disturbances in alpine forests can reduce forest cover or change the structure of the forest and consequently reduce the protective effect of forest against natural hazards such as avalanches and rockfalls. In this review article, the effect of the main abiotic (forest fire, windthrow, ice break, snow break, avalanche and rockfall) and biotic (insects and pathogens) disturbances in protection forests are presented along with their potential influence on the protective effect of forest against avalanches and rockfalls. In general, natural disturbances negatively affect the protective effect of forest, especially in the case of large-scale and severe events, which in alpine areas are mostly caused by storms, bark beetle outbreaks, avalanches and forest fires. Climate change induced interactions between disturbances are expected to present challenges in the management of protection forests in the future.

Suitability of MODIS-based NDVI index for forest monitoring and its seasonal applications in Central Europe

Abstract The paper demonstrates the multipurpose application of the normalized difference vegetation index (NDVI) derived from MODIS products for forest monitoring across the Central-European macro-region Slovakia and Hungary (i.e., the Western Carpathians and Pannonian basin). Relationships between forest dynamics and NDVI were analysed and used for determining the onset of phenophases in spring and autumn and for the assessment of forest growth and health condition. To identify the phenophases, the NDVI profile during the year was established by fitting a double logistic sigmoid function to data and phenological metrics were developed based on the calculated extreme values of the sigmoid function and its derivatives. According to our analyses, leaf unfolding and leaf fall were significantly delayed or advanced in 2018 with the increase of altitude and latitude (p < 0.01). The longitudinal aspect was significant only in the autumn phenophase with earlier onset of leaf fall towards to the east. The duration of the growing season varied extensively within the region, mainly according to altitudinal and latitudinal occurrence of beech forests. Positive associations between annual tree-ring width and standardized summer NDVI were found for conifers at local scale. The highest correlation period was between July 12 and August 12 as the most critical periods for forest growth. Slight positive correlation can be observed during March – April that could be associated with the varying start of the growing seasons. In the forest health study, whereas NDVI values could well identify the location and extent of a recent forest damage due to a combination of snow break and wind break, an urgent demand for more detailed field data was obvious.

A Bayesian Belief Network Approach to Predict Damages Caused by Disturbance Agents

In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between environmental changes, forest management, and disturbance agents to support forest resource managers in adaptive management. Empirical data with a comprehensive coverage for modelling the susceptibility of forests and the impact of disturbance agents are rare, thus making probabilistic models, based on expert knowledge, one of the few modelling approaches that are able to handle uncertainties due to the available information. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that has become very popular to practitioners and scientists mainly due to considerations of risk and uncertainties. In this contribution, we present a development methodology to define and parameterize BBNs based on expert elicitation and approximation. We modelled storm and bark beetle disturbances agents, analyzed effects of the development methodology on model structure, and evaluated behavior with stand data from Norway spruce (Picea abies (L.) Karst.) forests in southern Austria. The high vulnerability of the case study area according to different disturbance agents makes it particularly suitable for testing the BBN model.

Changes of forest cover and disturbance regimes in the mountain forests of the Alps

Natural disturbances, such as avalanches, snow breakage, insect outbreaks, windthrow or fires shape mountain forests globally. However, in many regions over the past centuries human activities have strongly influenced forest dynamics, especially following natural disturbances, thus limiting our understanding of natural ecological processes, particularly in densely-settled regions. In this contribution we briefly review the current understanding of changes in forest cover, forest structure, and disturbance regimes in the mountain forests across the European Alps over the past millennia. We also quantify changes in forest cover across the entire Alps based on inventory data over the past century. Finally, using the Swiss Alps as an example, we analyze in-depth changes in forest cover and forest structure and their effect on patterns of fire and wind disturbances, based on digital historic maps from 1880, modern forest cover maps, inventory data on current forest structure, topographical data, and spatially explicit data on disturbances. This multifaceted approach presents a long-term and detailed picture of the dynamics of mountain forest ecosystems in the Alps. During pre-industrial times, natural disturbances were reduced by fire suppression and land-use, which included extraction of large amounts of biomass that decreased total forest cover. More recently, forest cover has increased again across the entire Alps (on average +4% per decade over the past 25–115years). Live tree volume (+10% per decade) and dead tree volume (mean +59% per decade) have increased over the last 15–40yearsin all regions for which data were available. In the Swiss Alps secondary forests that established after 1880 constitute approximately 43% of the forest cover. Compared to forests established previously, post-1880 forests are situated primarily on steep slopes (>30°), have lower biomass, a more aggregated forest structure (primarily stem-exclusion stage), and have been more strongly affected by fires, but less affected by wind disturbance in the 20th century. More broadly, an increase in growing stock and expanding forest areas since the mid-19th century have - along with climatic changes - contributed to an increasing frequency and size of disturbances in the Alps. Although many areas remain intensively managed, the extent, structure, and dynamics of the forests of the Alps reflect natural drivers more strongly today than at any time in the past millennium.

Integrating tree-ring and inventory-based measurements of aboveground biomass growth: research opportunities and carbon cycle consequences from a large snow breakage event in the Swiss Alps

The temporal variability of the forest sink is associated with high uncertainties in both its magnitude and the driving ecological and climatic processes. In this study, we assess the inter-annual variability (IAV) of carbon uptake using annually resolved aboveground biomass increment (ABI) estimates from 272 pseudorandomly sampled trees at a long-term monitoring plot in the dry valley of the Valais in Switzerland. Over the 1950–2011 period, the mean ABI is 86.8 g C m−2 year−1 with an IAV of ±31 %. The IAV is largely driven by hydrological conditions throughout the water year from previous August to current August (r SPEI = 0.56; 1st differenced r = 0.75, p < 0.001). During extremely dry years (such as 1972, 1976, 1998, and 2011), the carbon accumulation was reduced up to 63 % from the long-term mean. Furthermore, our analysis explores possible biases of annual ABI derived from manual band dendrometers in permanent plot inventories caused by water status related changes in tree size. During the snow breakage event in March 2012 and subsequent management activities, 17 % of the standing biomass was killed. We estimate that the remaining trees will take ~16 years to make up for the loss of this disturbance, assuming a similar growth rate of the remaining trees as during the previous 60 years and that a potentially drier climate and the increased water availability for the remaining trees will balance each other. We demonstrate that well-replicated, representative tree-ring datasets have a huge potential to complement shorter-term and lower-resolution forest inventory monitoring data. Integrating tree-ring and plot data allow one to gain knowledge about annual changes in forest productivity even before monitoring started and help ecosystem managers to better adapt their strategies.

Local neighborhood competition following an extraordinary snow break event: implications for tree-individual growth

Abstract: Sustainable forest management practices and the increased interest of plantation forestry in species mixtures require an understanding of individual-tree growth in complex and diverse forests. Individual-tree growth has been found to be affected by factors such as species identity and size of the target tree as well as of neighboring trees, neighbor density and abiotic factors. However, most of these studies have been conducted in plantations or mixed forests with a very limited number of species. We conducted our study in a subtropical forest in China, which was very species rich and highly heterogeneous with regard to topography (slope inclination and aspect, elevation) and successional status. Prior to our study the forest was subjected to an exceptional snow break event. We asked whether individual-tree basal area increment (BAI) over three growing seasons following the snow break event was related to local biotic and abiotic conditions. We hypothesized that individual-tree BAI is negatively affected by local neighborhood competition, positively affected by local neighborhood diversity, negatively related to slope inclination, and positively related to aspect to south. Individual-tree BAI of four different species was mainly affected by tree size, local neighborhood competition and species identity. Contrary to our expectations, we did not observe significant effects of local neighborhood functional diversity and abiotic conditions. However, we did find a negative effect of plot functional diversity on BAI. This finding may be explained by a negative correlation of plot functional diversity and snow break damage, which was observed in mid- and late-successional stages. The disturbance event did considerably change the competitive local neighborhood interactions by reducing competition, which increased the BAI of target trees in more disturbed/more diverse plots.

Development of vaporization process from young stands of Norway Spruce and European Beech after snow breakage

The extreme disturbance of the forest environment in the young experimental spruce stand in the Orlické Hory Mts after the snow breakage disaster in the winter of 2005/2006 became the impulse for the present study. 98% spruce trees were affected, the stand density decreased from 1550 to 950 trees per ha, the needle foliage of the stand was reduced to about 40%, and the stand canopy was markedly disturbed. The investigation consisted of two methodical procedures: the assessment of evapotranspiration of the forest stands (ET) based on continuous measuring of the water content in the root zone of the soil profile, and intermittent measuring of evaporation from the soil surface including the ground vegetation (Es). Comparative investigation was simultaneously done in a young experimental beech stand with minimum disturbance. ET totals (evaporation from the soil surface and ground vegetation Es + transpiration of trees T) were comparable in both stands (200 to 235 mm during the growing season). Until 2006, ET was � 10% higher in the spruce stand, whereas in 2007, ET was 10% higher in the beech stand. An extremely high increase of the soil surface evaporation (Es) was observed in a gappy spruce stand. Immediately after the disaster, maximum daily totals of evaporation ranged from 1.5 to 2.0 mm in the spring and summer 2006, while in the beechstand they reached half these values. In the following year 2007, with gradual weeds infestation of the stand gaps, whose cover extended to 80% in the summer and autumn, the values of Es in the spruce stand reached up to 3 mm per day, on warm summer days being on the level of the weed-infested clear felled area. In the same days, evaporation in a fully closed beech stand was usually 3 to 4 times lower. The evaporation from the soil surface and ground vegetation evidently substituted the reduced transpiration of the spruce broken canopy, if ET total did not change significantly.

Analysis of snow accumulation and snow melting in a young mountain spruce and beech stand in the Orlické hory Mts., Czech Republic

The paper evaluates snow accumulation and the intensity of snow melting in a young spruce and beech stand. The study was carried out at the Deštné field research station in the Orlické hory Mts. (altitude 900 m, WSW aspect) in winter seasons 2005/2006, 2006/2007 and 2007/2008. The process of snow accumulation and melting was markedly affected or disturbed by the nearly total damage to the spruce stand by top breakage due to the extreme load of wet snow. Winter 2005/2006 was characterized by extreme parameters of snowpack (maximum depth of snow in spruce 157 cm, in beech 164 cm, maximum snow water equivalent in spruce 819 mm, in beech 833 mm). From the aspect of the snow cover duration, winter 2006/2007 was below the average, winter 2007/2008 was average. With respect to the significant reduction of the spruce crown biomass after snow breakage in winter 2005/2006, no significant differences were noted either in snow depth or in snow water equivalent in the spruce and beech stands. The rate of snow melting in the spruce and beech stands was never higher than 50 mm per day. If the spring final stage of snow melting is not accompanied by intensive rainstorms, mountain coniferous and broadleaved forest ecosystems reduce the danger of stormflows and floods within the required degree.

Factors related to natural disturbances in mountain Norway spruce (Picea abies) forests in the Julian Alps

An analysis of natural disturbances in the Julian Alps was carried out in the Jelovica-Pokljuka region (9627 ha) for the period 1979–2006. Data from salvage cuttings were used to examine the occurrence of windthrow, snow break, and insect attack disturbances in relation to site and stand characteristics, previous disturbances, and forest management. Forest stands at the site were characterized by a high growing stock (400 m3-ha−1 on average) and a large proportion of Norway spruce (87%). Salvage cutting due to windthrow, snow break and insect attacks was strongly related to altitude, aspect, topographic position, diameter structure, developmental phase of the stands, and forest landscape heterogeneity. Pole stands were more susceptible to snow breakage and less susceptible to windthrow and insect attack. A more heterogeneous forest landscape increased the risk of windthrow and insect attack occurrence, while the severity of all natural disturbances was lower in more heterogeneous forest landscapes. Natural disturbances and previous cuttings also significantly influenced the likelihood of occurrence and the severity of subsequent disturbances. To improve stand resistance, forest management measures considering the silviculture system and thinning are discussed.

STUDY ON SEISMIC PERFORMANCE OF WOODEN HOUSES DURING STRONG GROUND MOTION IN SNOW SEASON

To examine relationship between dynamic behavior of roof snow and seismic response of wooden houses by strong ground motion, the authors carried out shaking table test. The structure of one-story and flat roof with steel sheet roofing was used as the model in the test. Harmonic vibration was used as seismic wave in the test. Adfreezing of roof snow and roof surface projection that restricted roof snow sliding was recreated in the model. Relationship between sliding restriction conditions and breaking form of roof snow was observed. Sliding conditions after roof snow break were recreated in the test that changed roof surface condition and roof snow weight. Relationship between friction resistance of sliding surface and response characteristics of the model was examined by the test. The roof snow break from weak layer and one section in wet snow might occur in strong ground motion. In the evaluation of seismic performance of wooden houses during snow season, necessity to consider the ground motion scale, sliding surface characteristics of roof snow was clarified.

Seventy-seven years of natural disturbances in a mountain forest area — the influence of storm, snow, and insect damage analysed with a long-term time series

We investigated the effects of site properties, forest structure, and time on snow breakage, insect outbreaks, windthrow, and total damage for predominantly planted forests. A time series of forest damage in southwestern Germany spanning 77 years, from 1925 to 2001, was available along with a database on site properties and forest structure. The statistical modeling procedure successively addressed (i) probability of damage occurrence, (ii) timber loss in damaging events, and (iii) interaction among damage agents over time. Logistic and linear regressions were combined with multivariate autoregressive techniques. Natural disturbances were responsible for a total timber loss of 3.0 m3· ha–1· year–1. The distribution of the timber loss values over the years and over sites and stands with different properties was modeled with a standard error of 6.7 m3· ha–1· year–1. Disturbances are more likely to occur in previously damaged stands. Storm events typically provoke subsequent insect outbreaks between 2 and 6 years later. Large windthrow and snow breakage events tend to occur periodically, once every 10th, 11th, or 15th year. Analysis of disturbances as a time series significantly enhances understanding of forest risk processes.

Predisposition assessment systems (PAS) as supportive tools in forest management—rating of site and stand-related hazards of bark beetle infestation in the High Tatra Mountains as an example for system application and verification

Natural disturbances such as bark beetle infestations, feeding of vertebrates, storm throw, or snow breakage constitute important determinants for decision-making processes in forest management. Knowledge concerning the mechanisms of disturbance agents and the spatial distribution of predisposed stands allows for both an optimized input of labor and financial resources in forest management and may support the definition of core areas and surrounding buffer zones in protected areas. In order to face the demand for tools that illuminate the complex causal relationships between disturbance agents and predisposing site and stand-related characteristics, knowledge-based expert models for hazard assessment were developed. Key factors for the predisposition of forests to diverse biotic and abiotic agents were identified by an extensive literature research and expert discussions, and summarized by way of checklists. We discuss the basic assumptions of our predisposition assessment systems (PAS), using the specific model for the eight-toothed spruce bark beetle ( Ips typographus) and the results of the system's application and verification in the High Tatra Mountains. We demonstrate that the spatial distribution of predisposing indicators significantly corresponds to the pattern of bark beetle attacks in the research area. The assessment system offers high flexibility of the underlying database and for spatial resolution, allows for a retrospective analysis of forest damages, for various possibilities of application (e.g., as a checklist, spatial analysis, etc.), and for easy incorporation of new scientific findings and empiric knowledge.

The influence of high waters on stream fish populations in regulated rivers

The hydrological regime of the originally, non-regulated Danube was characterised by a continuous swelling of the river due to snow break in the Alpes in spring time, which resulted in a high-water-period for several weeks. At that time, huge flood areas were inundated along the main channel, which play a major role as spawning areas for phytophilic fish species. The subsequently slow droping of the water levels during the summer months allowed the adults, larvae and juveniles to migrate into the main river or backwaters. Since 1870, this course of natural occurring fluctuations in waterlevels has been considerably altered by man-made regulation and canalization, which lead to a distinct increase of the rapidity of the high water events. For example: during the high water from August 1985, the water level increased within one day from 340 cm up to 780 cm in Vienna, and lasted only for four days. The question was addressed, to which extent the changing hydrological conditions are reflected in year-class strength of the fish populations.

Foliage loss due to snow, wind, and winter drying damage: its effects on leaf biomass of some western conifer forests

Damage to forest canopies by wind, snow, or winter desiccation significantly reduced stand leaf biomass and area below "steady-state" levels in several western coniferous forests. Leaf biomass of 12 different western conifer forests sampled for an average of 4 years was reduced by as much as 36.3, 34.5, and 42.2% by single wind damage, snow breakage, or winter desiccation events, respectively, during the sampling interval. Foliage loss exceeded annual foliage production as estimated from leaf litterfall in about half the stands where damage occurred. Production efficiency (Mg dry matter•ha−1•year−1•Mg−1 foliage) by remaining foliage appeared to increase after damage. Based on the data available, major canopy damage appears to occur at roughly 9- to 16-year intervals in western coniferous forests. However, this canopy damage is epidosic and unpredictable. Such damage adds an additional measure of uncertainty to forest productivity models.