Search Results (16)

In the southern taiga of Siberia, periodic outbreaks of the Siberian moth Dendrolimus sibrircus Tschetv. have been observed. The outbreaks result in the defoliation of Siberian fir Abies sibirica Ledeb. and Siberian pine Pinus sibirica Du Tour. stands across approximately one million hectares, leading to dieback of the affected forests. This is largely attributable to the inability to promptly identify the onset of the pest population growth in a timely manner, particularly in the context of expansive forest areas with limited accessibility. It is feasible to enhance the efficacy of monitoring Siberian moth populations by discerning stands with the highest propensity for damage and concentrating efforts on these areas. To achieve this, we employed machine learning techniques, specifically gradient boosting, support vector machines, and decision trees, training models on two sets of predictors. One of the datasets was obtained through a field study conducted in forest stands during the previous outbreak of the Siberian moth (2015–2018), while the other was derived from the analysis of remote sensing data during the same period. In both 2015 and 2016, the defoliation was most accurately predicted using gradient boosting (XGB algorithm), with ROC-AUC values reaching 0.89–0.94. The most significant predictors derived from the ground data were the proportions of Siberian fir, Siberian spruce Picea obovata Ledeb., and Scots pine Pinus sylvestris L., phytosociological data, tree age, and site quality. Among the predictors obtained from the analysis of remote sensing data, the distance to disturbed forest stands was identified as the most significant, while the proportion of dark coniferous species (A. sibirica, P. sibirica, or Picea obovata Ledeb.), the influx of solar radiation (estimated through the CHILI index), and the position in the relief (mTPI index) were also determined to be important. Full article

In this study, methods are proposed for analyzing the susceptibility of forest stands to attacks by forest insects on the basis of Earth remote sensing data. As an indicator of the state of forest stands, we proposed to use a parameter of the sensitivity of a vegetation index (normalized difference vegetation index; NDVI) during a vegetative period to changes in the radiative temperature of the territory (land surface temperature; LST) determined from satellite data of the Terra/Aqua system. The indicator was calculated as a spectrum of a response function in an integral equation linking changes of NDVI to those of LST. Backtesting was carried out using data from two outbreaks of the Siberian silk moth Dendrolimus sibiricus Tschetv. and outbreaks of the white mottled sawyer Monochamus urussovi Fischer and of the four-eyed fir bark beetle Polygraphus proximus Blandford in taiga forests of Krasnoyarsk Territory in Russia. In addition, the state of fir stands in the year 2023 was examined when damage to the forest stands was not yet noticeable, but Siberian silk moth adults were found in pheromone traps. It was shown that the proposed indicator of susceptibility of forest stands changed significantly 2–3 years before the pest outbreak in outbreak foci of the studied areas. Thus, the proposed indicator can be used to predict outbreaks of insect pests. The proposed approach differs from commonly used remote sensing methods in that, rather than using absolute values of remote indicators (such as, for example, NDVI), it focuses on indicators of the susceptibility of these remote indicators to the characteristics of the natural environment. Since any given point on the planet is characterized by a seasonally varying temperature, it is always possible to determine the sensitivity of a remote sensing indicator to changes in the environment that are not directly related to the absolute value of the indicator. Future studies are expected to examine susceptibility indices as a function of forest stand location and species, and to examine the length of spatial correlation of susceptibility indices, which may provide information on the possible extent of future insect outbreaks. Full article

This study presents an approach to forecast outbreaks of Dendrolimus sibiricus, a significant pest affecting taiga ecosystems. Leveraging comprehensive datasets encompassing climatic variables and forest attributes from 15,000 taiga parcels in the Krasnoyarsk Krai region, we employ genetic programming-based predictive modeling. Our methodology utilizes Random Forest algorithm to develop robust forecasting model through integrated data analysis techniques. By optimizing hyperparameters within the predictive model, we achieved heightened accuracy, reaching a maximum precision of 0.9941 in forecasting pest outbreaks up to one year in advance. Full article

The Siberian moth, Dendrolimus sibiricus Tschetv., 1908 (Lepidoptera: Lasiocampidae) is a conifer pest that causes unprecedented forest mortality in Northern Asia, leading to enormous ecological and economic losses. This is the first study summarizing data on the parasitoid diversity and parasitism of this pest over the last 118 years (1905–2022). Based on 860 specimens of freshly reared and archival parasitoids, 16 species from two orders (Hymenoptera and Diptera) were identified morphologically and/or with the use of DNA barcoding. For all of them, data on distribution and hosts and images of parasitoid adults are provided. Among them, the braconid species, Meteorus versicolor (Wesmael, 1835), was documented as a parasitoid of D. sibiricus for the first time. The eastern Palaearctic form, Aleiodes esenbeckii (Hartig, 1838) dendrolimi (Matsumura, 1926), status nov., was resurrected from synonymy as a valid subspecies, and a key for its differentiation from the western Palaearctic subspecies Aleiodes esenbeckii ssp. esenbecki is provided. DNA barcodes of 11 parasitoid species from Siberia, i.e., nine hymenopterans and two dipterans, represented novel records and can be used for accurate molecular genetic identification of species. An exhaustive checklist of parasitoids accounting for 93 species associated with D. sibirisus in northern Asia was compiled. Finally, the literature and original data on parasitism in D. sibiricus populations for the last 83 years (1940–2022) were analysed taking into account the pest population dynamics (i.e., growth, outbreak, decline, and depression phases). A gradual time-lagged increase in egg and pupal parasitism in D. sibiricus populations was detected, with a peak in the pest decline phase. According to long-term observations, the following species are able to cause significant mortality of D. sibiricus in Northern Asia: the hymenopteran egg parasitoids Telenomus tetratomus and Ooencyrtus pinicolus; the larval parasitoids Aleiodes esenbeckii sp. dendrolimi, Cotesia spp., and Glyptapanteles liparidis; and the dipteran pupal parasitoids Masicera sphingivora, Tachina sp., and Blepharipa sp. Their potential should be further explored in order to develop biocontrol programs for this important forest pest. Full article

During the growth of a forest insect outbreak epicenter, there are processes that involve the formation and expansion of the primary epicenter of forest damage, as well as secondary epicenters—both connected and unconnected to the primary one. This study characterizes outbreak epicenters in terms of their fractal dimensions and “viscous finger” parameters at the epicenter boundary, highlighting their significance in the context of forest insect management. Local outbreak epicenters were found to be characterized by fractal dimension D = 1.4–1.5, and the boundaries of the epicenters were described using the “viscous finger” model. Proposed models were constructed and validated using remote sensing data obtained from MODIS and Sentinel-2 satellites at epicenter sites and boundaries during the outbreak of the Siberian silk moth Dendrolimus sibiricus Tschetverikov from 2014 to 2020 in the Krasnoyarsk region of Russia. The study revealed that the frequency of the mode spectrum of one-stage spatial series of “viscous fingers” corresponds with the data on the development of the outbreak foci area. Full article

The feasibility of risk assessment of a Siberian silk moth (Dendrolimus sibiricus Tschetv.) outbreak was analyzed by means of landscape and weather characteristics and tree condition parameters. Difficulties in detecting forest pest outbreaks (especially in Siberian conditions) are associated with the inability to conduct regular ground surveillance in taiga territories, which generally occupy more than 2 million km². Our analysis of characteristics of Siberian silk moth outbreak zones under mountainous taiga conditions showed that it is possible to distinguish an altitudinal belt between 400 and 800 m above sea level where an outbreak develops and trees are damaged. It was found that to assess the resistance of forest stands to pest attacks, researchers can employ new parameters: namely, characteristics of a response of remote sensing variables to changes in land surface temperature. Using these parameters, it is possible to identify in advance (2–3 years before an outbreak) forest stands that are not resistant to the pest. Thus, field studies in difficult-to-access taiga forests are not needed to determine these parameters, and hence the task of monitoring outbreaks of forest insects is simplified substantially. Full article

Recently, we found that the spongy moth Lymantria dispar L. is susceptible to infection by a Dendrolimus sibiricus cytoplasmic polyhedrosis virus (DsCPV-1). In the present study, we evaluated the pathogenicity of DsCPV-1 against L. dispar larvae and its impact on surviving insects after the infection. Offspring of virally challenged insects were tested for susceptibility to a stress factor (starvation). In addition, we used light microscopy and quantitative polymerase chain reaction (qPCR) to test the ability of DsCPV-1 to be transmitted vertically. We found insect mortality of the L. dispar parents following the infection was positively associated with DsCPV-1 dose. DsCPV-1 was lethal to second-instar L. dispar larvae with a 50% lethal dose (LD₅₀) of 1687 occlusion bodies per larva. No vertical transmission of DsCPV-1 to offspring larvae was detected, while the majority of insect deaths among offspring larvae were caused by microsporidia (Vairimorpha lymantriae), which was harbored by the parents. The offspring of virally challenged parents exhibited a higher number of detected microsporidia compared to the control. Our findings suggest that the application of DsCPV-1 is effective in controlling pests in terms of transgenerational impact following virus exposure. Full article

Three models of abundance dynamics for forest insects that depict the development of outbreak populations were analyzed. We studied populations of the Siberian silkmoth Dendrolimus sibiricus Tschetv. in Siberia and the Far East of Russia, as well as a population of the pine looper Bupalus piniarius L. in Thuringia, Germany. The first model (autoregression) characterizes the mechanism where current population density is dependent on population densities in previous k years. The second model considers an outbreak as analogous to a first-order phase transition in physical systems and characterizes the outbreak as a transition through a potential barrier from a low-density state to a high-density state. The third model treats an outbreak as an effect of stochastic resonance influenced by a cyclical factor such as solar activity and the “noise” of weather parameters. The discussion focuses on the prediction effectiveness of abundance dynamics and outbreak development for each model. Full article

This study analyzed the relationship between characteristics of annual tree ring time series and the intensity of attacks on forest stands by forest insects. Using tenets of the fluctuation–dissipation theorem (which is widely used in physics), time series parameters are proposed that can help to assess the susceptibility of a forest stand to insect pests. The proposed approach was applied to evaluate differences in parameters of tree ring widths among outbreaks of the pine looper, Siberian silk moth, and spongy moth. A comparison of trees characteristics between outbreak locations and undamaged forest stands (control) showed that the tested parameters statistically significantly differed between the outbreak locations and control stands and can be used to assess the risk of pest outbreaks in forest stands. Full article

The characteristics of Abies sibirica Ledeb.- and Pinus sibirica Du Tour dominated forests stands in outbreak spots formed during a Dendrolimus sibiricus outbreak in 2014–2017 were studied at the stage of population collapse (east of the West Siberian Plain and western foothills of the Yenisei Range). The research was based on the data obtained during ground surveys conducted in 2016 when stands characteristics, the Siberian silk moth population density, and defoliation level were recorded. We classified the studied stands using decision trees and random forest algorithms to identify the key characteristics that determine the formation of outbreak spots. The classification results showed that the characteristics of the detected outbreak spots differ significantly from those previously described for dark coniferous stands of the southern taiga in Siberia. The highest probability of the outbreak spot occurrence in the study area was revealed for stands with the following characteristics: moderately moist site; Siberian stone pine and Siberian fir take 40% or more of stem volume; age of less than 105 years. Another group of forest stands under threat are those sharing the following characteristics: large area (more than 60 ha); stand homogeneity; ground vegetation is dominated by feather mosses; age of more than 120 years; Picea obovata Ledeb. takes a significant share in a stem volume. Such characteristics indicate that during the population collapse, the Siberian silk moth forms outbreak spots in stands that either undergo an early successional stage after previous outbreak or have been slightly damaged during the previous outbreaks due to unfavorable habitat conditions. Full article

In this study, we have analyzed tree stand disturbance by hthe Siberian Silk Moth (Dendrolimus sibiricus Tschetverikov (Lepidoptera: Lasiocampidae)) in Central Siberia (Krasnoyarsk region, Russia) in 2015–2020. We considered two plots that experienced silk moth outbreaks in 2015–2018 and 2018–2020 and used satellite data (Terra/MODIS, Landsat/ETM/OLI), field forest inventory data, a meteorological data set, and a vegetation cover vector layer. Silk moth-disturbed areas were classified using NDVI, which was calculated for each 15-day period during the growing season (April–September). We obtained formalized descriptions of the temporal dynamics of the disturbed area. Next, we classified the degree of disturbance of the forest stand after the impact of the silk moth by the threshold method according to the ranges of NDVI anomalies. Based on the generalized data from the forest inventory, we performed a correlation analysis of the relationship between the main characteristics of forests and the classes of disturbance. Finally, using a series of regression equations, we described a procedure for predicting the degree of impact on the stand during the time of silk moth outbreaks in the dark-needle coniferous stands of Central Siberia. Full article

In this study, we have analyzed the spatial dynamics of the forests disturbed by Siberian Silk Moth (Dendrolimus sibiricus Tschetverikov (Lepidoptera: Lasiocampidae)) in Central Siberia and obtained model equations that fit these dynamics. We considered three sites that experienced silk moth outbreaks in 1993–1996, 2015–2018, and 2018–2020 and used satellite data (NOAA/AVHRR, Terra/MODIS, Landsat/ETM/OLI), field data, a digital elevation model, and maps of predominant forests. Silk moth-disturbed areas were classified using NDVI, which was calculated for each 15-day period during the growing season (April–September). Time series of disturbed forest areas were obtained for three sites located in the Krasnoyarsk region (Central Siberia, Russia). Total damaged areas for these sites were 41, 430, and 470 thousand hectares. We obtained formalized descriptions for the temporal dynamics of the disturbed area. Full article

The consecutive occurrence of drought and insect outbreaks could lead to cumulative, negative impacts on boreal forest productivity. To disentangle how both stressors affected productivity, we compared changes in tree canopy cover and radial growth after a severe outbreak in Siberian spruce (Picea obovata) southern taiga forests. Specifically, we studied the impacts of the 2012 severe drought followed by a Siberian silk moth (Dendrolimus sibiricus, hereafter SSM) outbreak, which started in 2016, on spruce forests by comparing one non-defoliated site and two, nearby fully defoliated sites, using remote sensing and tree-ring data. The SSM outbreak caused total defoliation and death of trees in the infested stands. We found a sharp drop (–32%) in the normalized difference infrared index and reduced radial growth in the defoliated sites in 2018. The growth reduction due to the 2012 drought was –37%, whereas it dropped to 4% of pre-outbreak growth in 2018. Tree growth was constrained by warm and dry conditions from June to July, but such a negative effect of summer water shortage was more pronounced in the defoliated sites than in the non-defoliated site. This suggests a predisposition of sites where trees show a higher growth responsivity to drought to SSM-outbreak defoliation. Insect defoliation and drought differently impacted taiga forest productivity since tree cover dropped due to the SSM outbreak, whereas tree growth was reduced either by summer drought or by the SSM outbreak. The impacts of abiotic and biotic stressors on boreal forests could be disentangled by combining measures or proxies of canopy cover and radial growth which also allow the investigation of drought sensitivity predisposes to insect damage. Full article

Methods for analyzing the resistance of large woodlands (such as Siberian taiga forests) to insect attacks based on remote sensing data are proposed. As an indicator of woodland’s resistance, we suggest a function of normalized difference vegetative index (NDVI) susceptibility to changes in the land surface temperature (LST). Both NDVI and LST are obtained via the TERRA/AQUA satellite system. This indicator function was calculated as the spectral transfer function of the response in the integral equation connecting the changes in NDVI and LST. The analysis was carried out for two test sites, both of which are fir stands of the Krasnoyarsk region taiga zone. In the first case, the fir stands have suffered damage inflicted by Siberian silk moth caterpillars, Dendrolimus sibiricus Tschetv. since 2015. Adjacent intact fir forest areas were also analyzed. In the second case, the object of the study was a fir tree site damaged by Black Fir Sawyer Monochamus urussovii Fischer in 2013. It is demonstrated that the above-mentioned indicator function changed significantly 2–3 years prior to the pest population outbreaks, and therefore this indicator function can be used to assess the risk of pest population outbreak. Thereby, the proposed indicator compares favorably with vegetation cover estimates using NDVI, which register significant defoliation of tree stands and cannot be used for forecasting. Full article

This research is dedicated to solving an urgent problem associated with the large-scale destruction of taiga forests by Siberian silk moth (Dendrolimus sibiricus) outbreaks. The dynamics of the damage to dark coniferous forest stands induced by the Siberian silk moth outbreaks in mid-altitude mountains were studied. A hypothesis was formulated based on the fundamental influence of the orography on the phytophage’s dispersal within the landscape, along with the climate, which acts as a secondary predictor—a catalyst for outbreaks. The study was carried out using Landsat−8 satellite imagery time-series (from 2018 to 2020). The data were verified using a field forest pathological survey of the territory. An assessment of the defoliated forest area and damage association with the landscape was carried out using an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model. The assessment was aimed to detail the forecast parameters for an outbreak development in mid-altitude mountains using the orographic features—altitude, terrain slope, and slope aspect. Early warnings of phytophagous insect outbreaks in mountain southern taiga should be focused on the permanent monitoring of dark coniferous stands of the mossy group of forest types, covering altitude levels from 400 to 600 m, located on gentle terrains and slopes of up to 15 degrees. The greatest vulnerability to phytophage impacts was characterized as areas located at altitudes from 400 to 600 m. The upper limit of D. sibiricus distribution was 900 m above sea level. The results obtained provide comprehensive information on the Siberian silk moth potential reserves within the study area with the possibility of extrapolation to similar territories. The data will make it possible to model pest outbreaks based on orography and improve the forest pathological monitoring methods at the regional level. Full article