Search Results (12)

Climate change has intensified the frequency and severity of forest disturbances globally, including windthrow, which poses substantial risks for both forest productivity and ecosystem stability. Rapid and precise assessment of wind-induced tree damage is essential for effective management, yet many injuries remain visually undetectable in the early stages. This study employed drone-based multispectral imaging and a simulated wind stress experiment (static pulling) on Norway spruce (Picea abies (L.) Karst.) to investigate the detectability of physiological and structural changes over four years. Multispectral data were collected at multiple time points (2023–2024), and a suite of vegetation indices (the Normalised Difference Vegetation Index (NDVI), the Structure Insensitive Pigment Index (SIPI), the Difference Vegetation Index (DVI), and Red Edge-based indices) were calculated and analysed using mixed-effects models. Our results demonstrate that trees subjected to mechanical bending (“Bent”) exhibit substantial reductions in the near-infrared (NIR)-based indices, while healthy trees maintain higher and more stable index values. Structure- and pigment-sensitive indices (e.g., the Modified Chlorophyll Absorption Ratio Index (MCARI 2), the Transformed Chlorophyll Absorption in Reflectance Index/Optimised Soil-Adjusted Vegetation Index (TCARI/OSAVI), and RDVI) showed the highest diagnostic value for differentiating between damaged and healthy trees. We found the clear identification of group- and season-specific patterns, revealing that the most pronounced physiological decline in Bent trees emerged only several seasons after the disturbance. Full article

Windthrow determines major changes in tree stand evolution due to the felling or breaking of either isolated trees or entire stands. It has a major ecological, social and economic impact. Wood loss resulting from tree felling and cross-cutting operations is a less-studied aspect related to windthrow. Wood loss is represented by high stumps, broken or split stems, wood lost in the felling of trees that remain standing, wood lost in felling cuts that attempt to remove the stem from the root plate of partially or totally uprooted trees and wood lost as a result of stem cross-cutting. The study focused on estimating losses and their indices in a spruce tree stand located in the Curvature Carpathians. Windthrow took place in this tree stand in February 2020. The results showed that the total wood loss index is 7.747%. The main losses are represented by wood losses in high stumps (5.319%). The amount of wood loss depends on the proportion of uprooted or standing trees, ground inclination and the uprooting direction of trees as opposed to ground inclination, as well as on tree dimension. Tree volume significantly influences wood loss in high stumps (p < 0.001). The closer the uprooting direction is to the highest slope, the higher the tree stump becomes. Wood loss caused by stem breaking and splitting represents 2.280%, tree felling cuttings and stem removal from the root plate in uprooted trees account for 0.138% while loss resulting from stem cross-cutting represents 0.10%. Full article

As the frequency of strong storms and cyclones increases, understanding wind risk in both existing and newly established plantation forests is becoming increasingly important. Recent advances in the quality and availability of remotely sensed data have significantly improved our capability to make large-scale wind risk predictions. This study models the loss of radiata pine (Pinus radiata D.Don) plantations following a severe cyclone within the Gisborne Region of New Zealand through leveraging repeat regional LiDAR acquisitions, optical imagery, and various surfaces describing key climatic, topographic, and storm-specific conditions. A random forest model was trained on 9713 plots classified as windthrow or no-windthrow. Model validation using 50 iterations of 80/20 train/test splits achieved robust accuracy (accuracy = 0.835; F1 score = 0.841; AUC = 0.913). In comparison to most European empirical models (AUC = 0.51–0.90), our framework demonstrated superior discrimination, underscoring its value for regions prone to cyclones. Among the 14 predictor variables, the most influential were mean windspeed during February, the wind exposition index, site drainage, and stand age. Model predictions closely aligned with the estimated 3705 hectares of cyclone-induced forest damage and indicated that 20.9% of unplanted areas in the region would be at risk of windthrow at age 30 if established in radiata pine. The resulting wind risk surface serves as a valuable decision-support tool for forest managers, helping to mitigate wind risk in existing forests and guide adaptive afforestation strategies. Although developed for radiata pine plantations in New Zealand, the approach and findings have broader relevance for forest management in cyclone-prone regions worldwide, particularly where plantation forestry is widely practised. Full article

Windstorms are forest disturbances which generate canopy gaps. However, their effects on Mediterranean forests are understudied. To fill that research gap, changes in tree, cover, growth and soil features in Pinus halepensis and Pinus sylvestris plantations affected by windthrows were quantified. In each plantation, trees and soils in closed-canopy stands and gaps created by the windthrow were sampled. Changes in tree cover and radial growth were assessed by using the Normalized Difference Vegetation Index (NDVI) and dendrochronology, respectively. Soil features including texture, nutrients concentration and soil microbial community structure were also analyzed. Windthrows reduced tree cover and enhanced growth, particularly in the P. halepensis site, which was probably more severely impacted. Soil characteristics were also more altered by the windthrow in this site: the clay percentage increased in gaps, whereas K and Mg concentrations decreased. The biomass of Gram positive bacteria and actinomycetes increased in gaps, but the biomass of Gram negative bacteria and fungi decreased. Soil gaps became less fertile and dominated by bacteria after the windthrow in the P. halepensis site. We emphasize the relevance of considering post-disturbance time recovery and disturbance intensity to assess forest resilience within a multi-scale approach. Full article

This paper reports a semi-automated workflow for detection and quantification of forest damage from windthrow in an Alpine region, in particular from the Vaia storm in October 2018. A web-GIS platform allows to select the damaged area by drawing polygons; several vegetation indices (VIs) are automatically calculated using remote sensing data (Sentinel-2A) and tested to identify the more suitable ones for quantifying forest damage using cross-validation with ground-truth data. Results show that the mean value of NDVI and NDMI decreased in the damaged areas, and have a strong negative correlation with severity. RGI has an opposite behavior in contrast with NDVI and NDMI, as it highlights the red component of the land surface. In all cases, variance of the VI increases after the event between 0.03 and 0.15. Understorey not damaged from the windthrow, if consisting of 40% or more of the total cover in the area, undermines significantly the sensibility of the VIs to detecting and predicting severity. Using aggregational statistics (average and standard deviation) of VIs over polygons as input to a machine learning algorithm, i.e., Random Forest, results in severity prediction with regression reaching a root mean square error (RMSE) of 9.96, on a severity scale of 0–100, using an ensemble of area averages and standard deviations of NDVI, NDMI, and RGI indices. The results show that combining more than one VI can significantly improve the estimation of severity, and web-GIS tools can support decisions with selected VIs. The reported results prove that Sentinel-2 imagery can be deployed and analysed via web-tools to estimate forest damage severity and that VIs can be used via machine learning for predicting severity of damage, with careful evaluation of the effect of understorey in each situation. Full article

On the 29th of October 2018, a storm named “Vaia” hit North-Eastern Italy, causing the loss of 8 million m³ of standing trees and creating serious damage to the forested areas, with many economic and ecological implications. This event brought up the necessity of a standard procedure for windthrow detection and monitoring based on satellite data as an alternative to foresters’ fieldwork. The proposed methodology was applied in Carnic Alps (Friuli Venezia Giulia, NE Italy) in natural stands dominated by Picea abies and Abies alba. We used images from the Sentinel-2 mission: 1) to test vegetation indices performance in monitoring the vegetation dynamics in the short period after the storm, and 2) to create a windthrow map for the whole Friuli Venezia Giulia region. Results showed that windthrows in forests have a significant influence on visible and short-wave infrared (SWIR) spectral bands of Sentinel-2, both in the short and the long-term timeframes. NDWI8A and NDWI were the best indices for windthrow detection (R² = 0.80 and 0.77, respectively) and NDVI, PSRI, SAVI and GNDVI had an overall good performance in spotting wind-damaged areas (R² = 0.60–0.76). Moreover, these indices allowed to monitor post-Vaia forest die-off and showed a dynamic recovery process in cleaned sites. The NDWI8A index, employed in the vegetation index differencing (VID) change detection technique, delimited damaged areas comparable to the estimations provided by Regional Forest System (2545 ha and 3183 ha, respectively). Damaged forests detected by NDWI8A VID ranged from 500 m to 1500 m a.s.l., mainly covering steep slopes in the south and east aspects (42% and 25%, respectively). Our results suggested that the NDWI8A VID method may be a cost-effective and accurate way to produce windthrow maps, which could limit the risks associated with fieldwork and may provide a valuable tool to plan tree removal interventions in a more efficient way. Full article

Windthrows are the most important type of disturbance occurring in the forests of Central Europe. On 19 November 2004, the strong northeastern katabatic winds caused significant damage and land cover change to more than 126 km² of spruce forests in the Tatra National Park. The risk of subsequent soil erosion and accelerated runoff has increased in the affected habitats. Similar situations may reoccur this century as a consequence of climate change. A geographical approach and detailed research of the damaged area with more comprehensive statistical analyses of 47 independent variables will help us to obtain a deeper insight into the problem of windthrow disturbances. The results are based on a detailed investigation of the damaged stands, soil, and topography. A comprehensive input dataset enabled the evaluation of abiotic controls on windthrow disturbance through the use of a generalized additive model (GAM). The GAM revealed causal linear and nonlinear relationships between the local dependent quantitative variables (the damage index and the uprooting index) and independent variables (various soil and topography properties). Our model explains 69% of the deviance of the total damage. The distribution of the wind force depended upon the topographical position—mainly on the distance from the slope’s foot lines. The soil properties (mainly the soil skeleton, i.e., rock fragments in stony soils) affect the rate and manner of damage (uprooting), especially on sites with less wind force. Stem breakage with no relation to the soil prevailed in places with high force winds. The largest number of uprooted trees was recorded in localities without a soil skeleton. The spruce’s waterlogged shallow root system is significantly prone to uprooting. The comprehensive research found a significant relationship between the abiotic variables and two different measures of forest damage, and can expand the knowledge on wind impact in Central European forests. Full article

Natural disturbances (windthrow, bark beetle, and fire) have reduced forest cover in the Tatra National Park (Slovakia) by 50% since the year 2004. We analyzed carbon fluxes and streamflow ten years after the forest destruction in three small catchments which differ in size, land cover, disturbance type and post-disturbance management. Point-wise CO₂ fluxes were estimated by chamber methods for vegetation-dominated land-use types and extrapolated over the catchments using the site-specific regressions with environmental variables. Streamflow characteristics in the pre- and post-disturbance periods (water years of 1965–2004 and 2005–2014, respectively) were compared to identify changes in hydrological cycle initiated by the disturbances. Mature Norway spruce forest which was carbon neutral, turned to carbon source (330 ± 98 gC m⁻² y⁻¹) just one year after the wind disturbance. After ten years most of the windthrow sites acted as carbon sinks (from −341 ± 92.1 up to −463 ± 178 gC m⁻² y⁻¹). In contrast, forest stands strongly infested by bark beetles regenerated much slowly and on average emitted 495 ± 176 gC m⁻² year⁻¹. Ten years after the forest destruction, annual carbon balance in studied catchments was almost neutral in the least disturbed catchment. Carbon uptake notably exceeded its release in the most severely disturbed catchment (by windthrow and fire), where net ecosystem exchange (NEE) was −206 ± 115 gC m⁻². The amount of sequestered carbon in studied catchments was driven by the extent of fast-growing successional vegetation cover (represented by the leaf area index LAI) rather than by the disturbance or vegetation types. Different post-disturbance management has not influenced the carbon balance yet. Streamflow characteristics did not indicate significant changes in the hydrological cycle. However, greater cumulative decadal runoff, different median monthly flows and low flows and the greater number of flow reversals in the in the first years after the windthrow in two severely affected catchments could be partially related to the influence of the disturbances. Full article

The number of intense tropical cyclones is expected to increase in the future, causing severe damage to forest ecosystems. Remote sensing plays an important role in detecting changes in land cover caused by these tropical storms. Remote sensing techniques have been widely used in different phases of disaster risk management because they can deliver information rapidly to the concerned parties. Although remote sensing technology is already available, an examination of appropriate methods based on the type of disaster is still missing. Our goal is to compare the suitability of three different conventional classification methods for fast and easy change detection analysis using high-spatial-resolution and high-temporal-resolution remote sensing imagery to identify areas with windthrow and landslides caused by typhoons. In August 2016, four typhoons hit Hokkaido, the northern island of Japan, creating large areas of windthrow and landslides. We compared the normalized difference vegetation index (NDVI) filtering method, the spectral angle mapper (SAM) method, and the support vector machine (SVM) method to identify windthrow and landslides in two different study areas in southwestern Hokkaido. These methodologies were evaluated using PlanetScope data with a resolution of 3 m/px and validated with reference data based on Worldview2 data with a very high resolution of 0.46 m/px. The results showed that all three methods, when applied to high-spatial-resolution imagery, can deliver sufficient results for windthrow and landslide detection. In particular, the SAM method performed better at windthrow detection, and the NDVI filtering method performed better at landslide detection. Full article

For more than four centuries, the Tatra Mountains were affected by many factors, such as forest and pastoral management, mining and metallurgy, windthrows, snow avalanches, and bark beetle outbreaks. Due to the availability of the long-running Landsat program enabling acquisition of spatially and spectrally consistent information, it is possible to the use these data for forest disturbance analysis. The main aim of this study was to analyze the relationships between the frequency of disturbances detected over the period of 1985–2016 and selected topographic features, such as elevation, exposure, and slope, derived from a digital elevation model (DEM); stand features, such as vegetation community type, age, structure, and degree of naturalness of the stand; and the management protection zone, which was extracted from thematic layers of the Tatra National Park (TNP). Using the normalized difference moisture index (NDMI), we detected forest disturbances in each year and analyzed them in the context of these topographic features, forest stand characteristics, and the management protection zone. We observed that forest stands in the lower montane zone, slopes between 10°–30°, and eastern exposures were primarily affected by disturbances. These consisted of artificially planted spruce stands aged between 51 and 100 years old. Full article

Storm events are capable of causing windthrow to large forest areas. A rapid detection of the spatial distribution of the windthrown areas is crucial for forest managers to help them direct their limited resources. Since synthetic aperture radar (SAR) data is acquired largely independent of daylight or weather conditions, SAR sensors can produce temporally consistent and reliable data with a high revisit rate. In the present study, a straightforward approach was developed that uses Sentinel-1 (S-1) C-band VV and VH polarisation data for a rapid windthrow detection in mixed temperate forests for two study areas in Switzerland and northern Germany. First, several S-1 acquisitions of approximately 10 before and 30 days after the storm event were radiometrically terrain corrected. Second, based on these S-1 acquisitions, a SAR composite image of before and after the storm was generated. Subsequently, after analysing the differences in backscatter between before and after the storm within windthrown and intact forest areas, a change detection method was developed to suggest potential locations of windthrown areas of a minimum extent of 0.5 ha—as is required by the forest management. The detection is based on two user-defined parameters. While the results from the independent study area in Germany indicated that the method is very promising for detecting areal windthrow with a producer’s accuracy of 0.88, its performance was less satisfactory at detecting scattered windthrown trees. Moreover, the rate of false positives was low, with a user’s accuracy of 0.85 for (combined) areal and scattered windthrown areas. These results underscore that C-band backscatter data have great potential to rapidly detect the locations of windthrow in mixed temperate forests within a short time (approx. two weeks) after a storm event. Furthermore, the two adjustable parameters allow a flexible application of the method tailored to the user’s needs. Full article

Moderate severity disturbances, which only kill a subset of canopy trees (e.g., via insects, pathogens, and windthrow), are increasingly widespread in North America, and can alter forest structure and production. Whether the net primary production (NPP) of forest stands differing in pre-disturbance site quality and composition respond similarly to moderate severity disturbance, however, is unknown, but critical to understanding the disturbance response dynamics of patchy landscapes. We experimentally disturbed three, 2-ha stands varying in pre-disturbance primary production and community composition, temporarily reducing live stand basal area by 38% to 66% through the stem girdling of all mature early successional aspen (Populus tremuloides Michx. and Populus grandidentata Michx.) and birch (Betula papyrifera Marshall). Disturbance significantly altered stand-scale physical and biological structure and prompted a similar decade-long pattern of wood NPP decline and recovery. All stands exhibited an initial reduction in wood NPP, followed by a recovery period and eventual return to pre-disturbance levels within eight years, with the most productive stand exhibiting an increase in primary production following recovery. Following wood NPP recovery, more biologically diverse forest canopies with higher leaf area indexes intercepted more light, and, consequently, had higher rates of wood NPP. We conclude that, despite substantial pre-disturbance differences in productivity and community composition, relative wood NPP recovery patterns can be similar, though long-term post-recovery primary production may trend higher in more productive and compositionally diverse stands. We suggest that improved mechanistic understanding of different forest ecosystems’ responses to disturbances remains critical to informing management decisions across diverse landscape mosaics. Full article