Search Results (1,501)

The present study examines the effect of viruses on forest insects depending on the virus dose. Two model approaches are used to quantify the effect of viruses on insect survival. Both approaches describe the processes of virus exposure to insects within the framework of the second-order phase transition model, which is well known in theoretical physics. The first approach examines the temporal dynamics of larval survival at a given dose of virus exposure. This dependence is characterized by the time–effect curve. In this case, the lethal time of exposure LT100 is the time required for the death of all larvae in the experiment at a given dose D of exposure. The second approach describes the relationship between the proportion q_r of larvae that survived a fixed time T_c after the start of the experiment and the dose D of virus exposure. This dependence is characterized by the dose–effect curve. The experiments tested the effect of two different viruses—nucleopolyhedrovirus (NPV) and cypovirus (CPV)—on such insect species as Lymantria dispar L., Manduca sexta L. and Loxostege sticticalis L. It was shown that the proposed models of second-order phase transitions very accurately (with coefficients of determination of the models close to R² = 0.95) describe experiments on studying the effect of different virus strains on insect survival. The proposed models turned out to be useful for assessing the effectiveness of different virus strains against insect pests. Since the parameters of the second-order “dose–time” and “dose–effect” phase transition models are related to each other, it is possible to reduce the number of measurements of virus–insect interaction due to the relationship between these parameters, and instead of n observations of insect dynamics over time depending on the dose of exposure, the basic parameters characterizing the “virus–insect” interactions can be accurately estimated using only one measurement. It appears that the proposed model can be used to calculate the effect of toxic agents on the population of victims for a wide variety of toxicant species and populations. A sharp reduction in the labor intensity of experiments to assess the toxicity of certain toxicants on animal populations will simplify and reduce the cost of testing the response of living objects to toxicants. Full article

This study assesses the potential impact of sea level rise (SLR) on wood-consuming mills in coastal Georgia, a major forestry state in the southern United States. To assess the vulnerability of wood-consuming mills in coastal Georgia, two potential wood procurement zones are defined: areas within 40 miles (64.4 km) and 64 miles (103 km) of the radius of each wood-consuming mill. The projected SLR scenarios of 2 ft (0.61 m) and 6 ft (1.83 m)—approximating intermediate and high-end conditions for coastal Georgia, respectively—are then overlaid onto the procurement zones of each mill to calculate the percentage of procurement area lost to the inundation. Our findings indicate that a 2 ft rise would have a minimal impact on wood supply for most wood-consuming mills. On the other hand, some facilities in Glynn and Liberty Counties could experience a substantial loss of up to 26% of their wood procurement area under a 6 ft sea level rise with a 40-mile wood procurement zone due to proximity to inundation. A larger procurement radius of 64 miles mitigates this impact, though spatial variability persists. Woody wetlands suffer the highest proportional losses across buffers and scenarios; upland forest types remain mostly intact under 2 ft SLR and display moderate loss under 6 ft. This study emphasizes the significance of accounting for spatially variable climate change impacts when planning for mill resilience. The results inform long-term sustainability strategies for wood-consuming mills in coastal regions of Georgia and beyond. Full article

Objective: The objective was to evaluate the ability of Comprehensive Geriatric Assessment (CGA) parameters to predict all-cause mortality in older adults using both traditional statistical methods and machine learning (ML) approaches. Methods: A total of 1.974 older adults from a university hospital outpatient clinic were included in this study. Ninety-six CGA-related variables encompassing functional and nutritional status, frailty, mobility, cognition, mood, chronic conditions, and laboratory findings were assessed. Cox proportional hazards regression and six ML algorithms (logistic regression, support vector machine, decision tree, random forest, extreme gradient boosting, and artificial neural networks) were employed to identify mortality predictors. Model performance was evaluated using area under the curve (AUC), sensitivity, and F1-score. Results: During a median follow-up of 617 days (interquartile range [IQR]: 297–1015), 430 participants (21.7%) died. Lower Lawton instrumental activities of daily living scores, unintentional weight loss, slower gait speed, and elevated C-reactive protein levels were consistent mortality predictors across all models. The artificial neural network demonstrated the highest predictive performance (AUC = 0.970), followed by logistic regression (AUC = 0.851). SHapley Additive explanations (SHAP) analysis confirmed the relevance of these key features. Conclusions: CGA parameters provide robust prognostic information regarding mortality risk in older adults. Functional decline and inflammation markers offer greater predictive power than chronological age alone in assessing overall health and survival probability. Full article

Norway spruce (Picea abies (L.) H. Karst.) is a primary forest-forming species in the European part of Russia, both in terms of its distribution and economic importance. A number of studies indicate that one of the reasons for the disturbance of spruce forests is linked to rising temperatures, particularly the detrimental effects of extreme droughts. The aim of our research is to identify changes in the structural and functional organization of mature spruce forests at the center of the East European Plain. The study was conducted in intact spruce forests using resurveyed vegetation relevés within the Smolensk–Moscow Upland, with relevés repeated after 40 years (in 1985 and 2025). Changes in structural and functional parameters of spruce communities were analyzed. The results showed that significant disturbances of the tree layer led to changes in the vegetation of subordinate layers, as well as the successional dynamics of spruce forests. It was found that following the collapse of old-growth spruce stands, two types of secondary succession developed: (1) with the renewal of spruce and (2) with active development of shrubs (hazel and rowan) and undergrowth of broadleaved species. It was also demonstrated that the typological diversity of the studied communities changed over 40 years not only due to the loss of the tree layer and the formation of new “non-forest” types but also because several mixed spruce-broadleaved communities transitioned into broadleaved ones, and pine–spruce communities of boreal origin shifted to nemoral types. An analysis of the complete species composition of spruce forests based on Ellenberg’s scales scoring revealed changes in habitat conditions over the 40-year period. A noticeable trend was an increase in the proportion of thermophilic and alkaliphilic species, indicating a shift toward a nemoral vegetation spectrum. It is expected that under the current forest management regime, the next 40 to 60 years will see a decline in the proportion of spruce within mixed stands, potentially culminating in the complete collapse of monospecific spruce forests in the center of the East European Plain. Full article

Drought-induced forest mortality threatens biodiversity globally, particularly in arid, and semi-arid woodlands. The continual development of remote sensing approaches enables enhanced monitoring of forest health. Herein, we investigate the ability of a limited ground-truthed canopy dieback dataset and satellite image derived Normalised Difference Vegetation Index (NDVI) to make inferences about forest health as temporal and spatial extent from its collection increases. We used ground-truthed observations of relative canopy mortality from the Pinus edulis-Juniperus osteosperma woodlands of southeastern Utah, United States of America, collected after the 2017–2018 drought, and PlanetScope satellite imagery. Through assessing different modelling approaches, we found that NDVI is significantly associated with sitewide mean canopy dieback, with beta regression being the most optimal modelling framework due to the bounded nature of the variable relative canopy dieback. Model performance was further improved by incorporating the proportion of J. osteosperma as an interaction term, matching the reports of species-specific differential dieback. A time-series analysis revealed that NDVI retained its predictive power for our whole testing period; four years after the initial ground-truthing, thus enabling retrospective inference of defoliation and regreening. A spatial random forest model trained on our ground-truthed observations accurately predicted dieback across the broader landscape. These findings demonstrate that modest field campaigns combined with high-resolution satellite data can generate reliable, scalable insights into forest health, offering a cost-effective method for monitoring drought-impacted ecosystems under climate change. Full article

The health of ecosystems, their functionality and the fulfilment of ecosystem functions are all dependent on biodiversity and productivity. The ongoing transformation of forests is intensifying the need for conservation. At the same time, the herbaceous layer has not yet been studied enough by researchers. The aim of the study is to ascertain the impact of the composition and age of the stand of primary and secondary forests on the biomass and species diversity of the herbaceous layer in the most prevalent forest type of the Western Macroscline of the Southern Urals: moss spruce forests. The methodological basis was chosen to be genetic forest typology and generally accepted methods of studying forest vegetation. We studied primary dark coniferous forests, as well as secondary birch and aspen forests of different compositions and ages. Positive correlations with the age of the stand were found to be most pronounced for Oxalis acetosella L. and Lycopodium clavatum L., while negative correlations were found to be most pronounced for Deschampsia caespitosa (L.) P. Beauv., Brachypodium pinnatum (L.) Beauv., and Dactylis glomerata L. The positive correlations with the proportion of birch and aspen in the stand composition are most pronounced for Dactylis glomerata L., Geum rivale L., Aegopodium podagraria L., Aconitum septentrionale Koelle, and Prunella vulgaris L. The research results clearly demonstrate the length of time that changes in species composition and productivity of the herbaceous layer of mountain forests take place over. This must be considered when planning forest management and nature conservation in mountain forests in the Urals. On the one hand, our study is certainly regional, but on the other, similar forests, forest degradation, regenerative succession and the plant species studied are widespread in the boreal zone. Therefore, the research results will be of interest to many researchers whose work relates to forest resources, biodiversity conservation and forest succession. To expand the scope of the research, further studies are planned in other types of forest in the Ural Mountains. Full article

Understanding the determinants of crash injury severity is essential for developing effective safety strategies and reducing traffic-related losses. This study proposes a hybrid analytical framework that integrates interpretable machine learning with statistical modeling to address the limitations of existing approaches. A Random Forest (RF) classifier, combined with Shapley Additive Explanations (SHAP), was first employed to capture nonlinear relationships and identify key predictors of injury outcomes, including safety equipment, age, gender, and the presence of fixed obstacles. Random Forest was chosen for its strong predictive performance in capturing nonlinear relationships, while SHAP provides transparent explanations of model predictions. To ensure statistical rigor and quantify associations, a Partial Proportional Odds (PPO) model was subsequently applied, allowing for the relaxation of the proportional odds assumption (POA) and enabling the estimation of marginal effects. The results consistently highlight the protective role of safety equipment and the increased risks associated with fixed obstacles, adverse weather, and nighttime conditions. For instance, seatbelt use is associated with a 29.61% higher probability of no injury, whereas fixed obstacles are associated with a 29.36% lower probability and a higher risk of severe injury. These findings support safety campaigns that encourage protective equipment use and infrastructure policies aimed at reducing roadside obstacles and improving nighttime visibility. Future research will focus on accounting unobserved heterogeneity and validating the framework across multi-regional datasets to improve its generalizability and policy relevance. Full article

The cooling effect of urban forests has been widely investigated to support climate-adaptive spatial planning. However, studies on the impacts of key landscape drivers have often produced conflicting results, limiting their practical applicability. These inconsistencies may stem from an oversimplified focus on the global effects of individual factors, while neglecting non-linear threshold behaviors and pairwise interactions. To address this gap, this study employed an interpretable machine learning framework (XGBoost-SHAP) to quantify the seasonal non-linearities, thresholds, and interaction effects of landscape drivers on urban forest cooling in Suzhou, a subtropical Chinese city. The results indicate that the combined explanatory power of neighboring water body proportion (NWP), neighboring green space proportion (NGP), vegetation density (NDVI), spatial characteristics (Area, SHAPE), and elevation on the cooling intensity of urban forest patches was strongest in summer (R² = 0.615) and weakest in winter (R² = 0.316). Among these, NWP, NGP, and NDVI were the dominant drivers, while patch area and shape exhibited weaker marginal effects. NWP significantly enhances cooling only after exceeding seasonal critical thresholds (11%–15%). NGP contributed positively above ~40% in warm seasons but suppressed cooling above 37% in winter. Patch area exhibits a logarithmic relationship with cooling intensity, with a critical threshold of approximately 2.48 ha and saturation thresholds between 12 and 14 ha. SHAPE exerted positive effects in spring and winter, negative effects in summer, and a transition from negative to positive in autumn. Notably, significant, threshold-modulated interactions were identified, including those between NDVI and NWP, SHAPE and NDVI, SHAPE and NGP, NWP and NDVI, NWP and NGP, and NGP and NDVI. In each interaction, the first factor regulates and reverses the effect of the second once specific thresholds are exceeded. This study provides actionable, evidence-based guidance for the planning and optimized design of urban forests. Full article

The European spruce bark beetle, Ips typographus (Linnaeus, 1758), poses a significant threat to Picea abies (Linnaeus) Karsten, 1881 forests, with outbreaks often exacerbated by abiotic disturbances like the 2018 Vaia windstorm in the Italian Alps. Pheromone-baited traps are widely used for control, yet their overall efficacy and potential side effects, particularly the incidental capture of non-target insects, remain debated. This study aimed to comprehensively assess the presence and composition of non-target insects in I. typographus pheromone traps, used for both mass-trapping and monitoring, in the affected Alpine regions. We took into account single monitoring traps (dry collection) and three-trap cross configurations for mass-trapping (with preservative liquid), collecting and morphologically identifying insect by-catch. Our results revealed a non-target proportion (excluding bark beetles) significantly higher in mass-trapping (4.15%) compared to monitoring (1.00%), with approximately half being natural enemies of bark beetles. Crucially, we report that bark beetle parasitoids were repeatedly caught, with Tomicobia seitneri (Ruschka, 1924) (the third most abundant non-target species) particularly well represented, and Ropalophorus clavicornis (Wesmaël, 1835) also detected, which is noteworthy given its ecological role despite its lower numbers. Our findings underscore the significant, previously underreported, capture of beneficial parasitoids and highlight the need for careful consideration of non-target catches in I. typographus pest management strategies. Full article

Insect pre-dispersal seed predators attack a large proportion of the acorn crops in oak forests worldwide. Oaks (Quercus spp.) have evolved several strategies, including physical barriers, chemical defenses (e.g., tannins), and/or phenological predator avoidance, to reduce infestation rates. This study examines how four Mediterranean oak species cope with acorn-feeding insects. Nearly 4000 acorns were collected from five sites at two time points during the maturation period: in mid-September and mid-October. Infestation rates were higher in mid-September, when the pericarp is softer and easier to drill, but at that time, the cotyledon tannin content was higher. Q. coccifera acorns had the highest tannin concentration, which, we experimentally discovered, hampered weevil development (with longer development and a lower final larval mass). Infested acorn abscission was also more effective in Q. coccifera. Due to the smaller size and later maturation phenology of its acorns, insects depleted the cotyledons and suffered food shortages more frequently. In the end, Q. coccifera showed the lowest acorn infestation rates, although its strategy would have costs in further stages of the regeneration cycle. Tannins deter acorn dispersers, and their production is costly. Such trade-offs would favor the co-existence of different strategies evolved by Quercus spp. against pre-dispersal insect predators. Full article

Conflicts in freeway interchange diverging areas remain poorly understood, particularly their characteristics and severity determinants. To address this gap, we extracted over 20,000 vehicle trajectories from UAV footage at 16 interchange divergence zone across five multi-lane expressways using a YOLOX–DeepSORT method. From these trajectories, we identified longitudinal and lateral conflicts and classified their severity into minor, moderate, and severe levels using a two-dimensional extended time-to-collision metric. Subsequently, we incorporated 19 macroscopic traffic-flow and microscopic driver-behavior variables into four conflict-severity models–multivariate logistic regression, random forest, CatBoost, and XGBoost—and conducted to identify the key determinants of conflict severity based on the optimal models. The results indicate that lateral conflicts last longer and pose higher collision risks than longitudinal ones. Furthermore, moderate conflicts are most prevalent, whereas severe conflicts are concentrated within 300 m upstream of exit ramps. Specifically, for longitudinal conflicts, the most influential factors include speed difference, target-vehicle speed, truck involvement, traffic density, and exit behavior. In contrast, for lateral conflicts, the most critical factors include lane-change frequency, speed difference, target-vehicle speed, distance to the exit ramp, and truck proportion. Overall, these findings support the development of hazardous-driving warning systems and proactive safety management strategies in interchange diverging areas. Full article

The conservation of plant species requires detailed knowledge of their reproductive behaviour and population demographic structure. This is particularly important for species such as Cardamine bulbifera, which depend on old-growth forest habitats and rely predominantly or entirely on vegetative reproduction through axillary bulbils. Although C. bulbifera has a wide native range, little is known about its population structure and dynamics. The aim of this study was to assess the demographic composition, density and main traits of C. bulbifera individuals in six populations occurring in three types of forest habitats in southern Lithuania: Fennoscandian hemiboreal natural old broadleaved deciduous forests, Fennoscandian herb-rich forests with Picea abies and Galio-Carpinetum oak–hornbeam forests. Field studies were conducted in 2023, during which a total of 20 sampling plots (each 1 m²) were analysed in each population, arranged in a transect. The study revealed an absolute dominance of young (juvenile and immature) individuals in the populations (89.2%), whereas mature individuals comprised only a small fraction (10.8%). The proportion of mature individuals was significantly larger in hornbeam forests than in the other two forest types. The highest density of individuals was recorded in broadleaved forest, while the lowest density was found in spruce forest habitat. Mature C. bulbifera individuals in hornbeam habitats were significantly taller and had longer inflorescences than those in other habitats. The highest mean number of bulbils was produced by individuals of the studied species in spruce habitats, while bulbil production was lowest in hornbeam habitats. The strongest negative contribution to the number of C. bulbifera individuals was the area of bare soil in the sampling plot, whereas herb cover had the strongest positive effect. These results highlight habitat-specific differences in C. bulbifera population structure and suggest that the long-term viability of its populations is closely associated with forest type, as well as stability of the habitat and plant community. The optimum habitat conditions for C. bulbifera are found in old broadleaved forests, and habitats with natural succession are the most favourable for its growth and conservation. Full article

Crown defoliation in trees is one of the indicators of forest tree vitality, and a primary criterion for selecting trees for sanitary felling. In Croatia, the selection of trees for sanitary felling includes all dead trees and those with crown defoliation greater than 60% (defoliation class 3a); in the past, the threshold for marking trees for sanitary felling was above 80% (class 3b). The aim of this study was to analyze tree mortality in pedunculate oak (Quercus robur), silver fir (Abies alba), and European beech (Fagus sylvatica), as well as crown regeneration, i.e., the reduction in defoliation. The analysis included a total of 7975 trees, comprising 1182 silver fir, 4221 European beech, and 2572 pedunculate oak trees, covering the period from 1998 to 2023. The mortality rate was 7.2% for silver fir, 2.16% for beech, and 9.6% for oak. The percentage of trees that regenerated their crowns or reduced defoliation to below 60% was 17.01% for fir, 4.33% for beech, and 12.51% for oak. Considering the proportion of silver fir and pedunculate oak trees whose defoliation decreased to below 60%, a defoliation threshold greater than 80% would be a more appropriate criterion for sanitary felling, except for European beech trees, for which there is a minimal difference between the recovery rates in classes 3a and 3b. Full article

Wildfire activity is intensifying globally as climate change amplifies heat waves, droughts and wind extremes, threatening biodiversity. South Korea (63% forested) has experienced a sharp rise in large fires. We analysed 905 wildfires ≥ 5 ha from 1980–2024, linking burned area to maximum wind speed, relative humidity, temperature and forest structure (conifer, broadleaf and mature–stand ratios, forest cover). Pearson correlations, HC3-corrected regression, a 1000-tree Random Forest and five-fold validated XGBoost interpreted with SHAP captured linear and nonlinear effects; WUI influences were examined qualitatively. Each 1 m s⁻¹ increase in peak wind expanded burned area by ~8.5 ha, whereas a 1% rise in humidity reduced area by ~3 ha (p < 0.01). Broadleaf prevalence restrained spread, while high conifer and mature–stand proportions enlarged it. Machine learning raised explanatory power from R² = 0.62 to 0.66 and showed that very dry air, strong winds and conifer cover above half the landscape coincided with the largest events. Burned area during 2020–2024 reached 29,905 ha—sevenfold that of 2015–2019. These results imply that extreme fire weather, flammable pine fuels and expanding WUI settlements jointly elevate risk; implementing real-time meteorological thresholds, targeted fuel treatments and stricter WUI zoning can help mitigate this risk. Full article

Impatiens parviflora DC. occurs in various plant communities. Its occurrence has been confirmed in Poland across 13 natural habitats protected under the Habitats Directive. The aim of our work is to determine the differences between the plots with and without I. parviflora in terms of the species richness and ecological conditions of the 9180* habitat-type forest. Using data from 315 plots on which a phytosociological relevés was carried out, we analyzed the geographical variability, the Shannon-Winner index and the indicator species for old forests. Flora diversity was represented using the DCA, and the IndVal index was calculated to determine the species that best characterize the differentiated groups. The highest percentage of monitoring plots with I. parviflora is located in the Sudetes Mountains (67.7%) and the lowest in the Bieszczady Mountains (7.5%). Plots with I. parviflora were characterized by significantly lower tree cover, a higher number of tree species in the stand, a lower height of both the understory and herb layer and a lower number of old forest species. Impatiens parviflora does not affect the total number of species in the understorey but is associated with a lower proportion of species typical of old forests. The presence of I. parviflora also correlates with a higher proportion of young trees in the understorey, suggesting a link with successional processes and habitat disturbance. The spread of I. parviflora is limited by shade-loving trees such as Abies alba Mill. and Fagus sylvatica L. The diversity of the distribution of I. parviflora depends on local conditions, so conservation efforts should take into account the local ecological context. Full article