Search Results (314)

Disturbance events and subsequent management practices significantly shape the ecological legacies of affected sites. This study evaluated the impacts of a 2022 derecho and the subsequent forest management on forest structure and arthropod diversity by comparing affected forests at Fogwell Forest Nature Preserve and Fox Island County Park with control forests at Blue Cast Springs and Hammer Wald Nature Preserves. Arthropod communities were sampled using pitfall traps, while forest structure was assessed through detailed surveys of understory, midstory, and overstory vegetation. Results indicated a decrease in overall arthropod diversity across all sites since 2016, variably attributed to forest maturation, climatic variability, and the 2022 disturbance, with some taxa showing declines, such as Formicidae and Curculionidae. Fogwell exhibited a significant decline in arthropod diversity, likely linked to the derecho, while Fox Island’s diversity aligned more closely with undisturbed control sites. Notable midstory reductions were observed across sites over time, especially at Fox Island, due to harvest and storm impacts. Meanwhile, overstory diversity varied between properties. Regression modeling revealed that forest management practices at Fox Island may have mitigated the disturbance’s effects, aiding arthropod recovery. All in all, these findings highlight the importance of forest management strategies in influencing biodiversity and ecological recovery post-disturbance. Full article

Understory vegetation communities in chestnut (Castanea sativa L.) forests feature unique biodiversity patterns and high conservation value, yet the complex drivers of these communities remain poorly quantified. This study investigates the combined effects of structural, microclimatic, and topographic parameters on understory biodiversity in the mountainous region of Chalkidiki, Northern Greece. Using a nested plot design (n = 30), we integrated analytical in situ microclimatic monitoring with hemispherical photography (HemiView canopy image analysis system) to accurately quantify canopy architecture (canopy cover and solar radiation parameters), while a detailed vegetation inventory of vascular plants was performed to determine plant community structure and composition. Generalized Additive Models (GAMs) were employed to model Shannon Diversity (H’) and a weighted rarity index (RSR) representing complementary aspects of understory biodiversity. Our results reveal that the tree slenderness of the dominant stand serves as a robust proxy for stand competition and compactness. Lower slenderness values, reflecting reduced overstory competition, were significantly associated with enhanced light availability and potentially with microclimatic stability, which in turn supported higher levels of species diversity and rarity. Distinct ecological trends were observed between diversity and rarity. Shannon diversity was highest in closed forest environments characterized by lower temperatures, low stand slenderness values, southern aspects, and lower elevations, with the final model explaining 66.1% of the variance (n = 27). In contrast, species rarity was primarily driven by stand slenderness and low disturbance levels (explaining 54.6% of the variance), with the majority of rare species occurring in undisturbed stands (n = 30). These findings suggest that targeted, low-intensity management for competition promotes structurally stable stands and microclimatic buffering, facilitating the preservation of understory biodiversity. Full article

Artificial shelterbelts in arid and semi-arid regions play a key role in controlling land degradation, regulating wind erosion, and maintaining ecological security. However, their long-term protective effectiveness increasingly depends on accurate degradation diagnosis and targeted management of aging and degraded stands. This study developed a comprehensive health assessment and degradation grading framework for poplar shelterbelts in the Kubuqi Desert, northern China, using an indicator system covering stand structure, community structure, soil conditions, health risks, and external disturbances. Indicator weights were determined using the entropy weight method, and degradation grades were classified by combining the technique for order preference by similarity to ideal solution (TOPSIS) model with the rank-sum ratio (RSR)–Probit method. The results showed that soil conditions and stand structure were the dominant dimensions distinguishing degradation status, with weights of 50.98% and 25.30%, respectively. Grade I, Grade II, Grade III, and Grade IV stands accounted for 21.88%, 25.00%, 34.38%, and 18.75% of the plots, respectively, indicating that lightly and moderately degraded stands were predominant. Degradation grades were also associated with changes in understory cover and surface soil nutrients, especially decreases in soil organic matter and alkali-hydrolyzable nitrogen. Based on these results, grade-specific management strategies were proposed, including conservation and maintenance, density regulation, assisted restoration, and near-natural transformation. This framework provides a practical basis for diagnosing degradation status and guiding the renewal and management of aging shelterbelts in arid sandy regions. Full article

Forest conversion from natural forests to secondary forests and plantations has significantly altered wildlife habitats in subtropical regions. However, the drivers of disparities in bird and mammal multidimensional diversity between these forest types remain poorly understood. We analyzed a four-year camera-trapping dataset to compare the taxonomic, functional, and phylogenetic diversity and community structure of birds and mammals. Our results indicated that forest conversion impacts biodiversity differently across taxa. Birds exhibited higher taxonomic and phylogenetic diversity in secondary forests than in plantations. A similar pattern was also evident for birds among different stand types. However, mammals exhibited considerable taxonomic diversity but showed higher phylogenetic diversity and structure in secondary forests. A similar pattern was also evident for mammals among different stand types. Beta diversity revealed significant differences in bird taxonomic composition and mammal phylogenetic composition between secondary and plantation forests. Furthermore, elevation primarily influenced bird taxonomic diversity, phylogenetic diversity and structure in secondary forests, whereas mammal functional diversity, phylogenetic diversity and structure were more sensitive to elevational changes in both secondary and plantation forests. These findings reveal that birds and mammals respond distinctively to forest conversion. We emphasize that management strategies must be group-specific. For birds, we recommend prioritizing the preservation of secondary forests as biodiversity refugia and transforming structurally simplified plantations into complex habitats by retaining legacy trees and native understory vegetation. For mammals, conservation should prioritize landscape-scale connectivity by protecting continuous forest corridors along altitudinal gradients. Practically, this requires restricting further fragmentation of high-altitude habitats and restoring native vegetation in degraded corridors to facilitate dispersal and maintain the phylogenetic integrity of mammal communities. Full article

Pine plantations on volcanic slopes in Indonesia are considered to be forests and are managed for wood production and slope protection. Logging practices followed by replanting may affect soil health. Existing agroforestry management contracts allow farmers to intercrop with vegetables in young plantations and grow fodder grasses in older ones. However, critical data on hydrological functions in such systems are scarce, while concerns over heavy rainfall and floods increase. We explored the relationships between soil cover, soil carbon, earthworms, soil porosity and infiltration rates in relation to slope class in second-rotation pine plantations around two years of age (intercropped) and at ten-year old pine-grass stages. Five slope classes (0%–8%, 8%–15%, 15%–25%, 25%–45%, and >45%) were compared with three measurement points each. Basic soil chemical and physical characteristics were measured for the 0–10, 10–20 and 20–30 cm layers. Remnant natural forest was available as a historical reference only on the steepest slope class. Organic soil carbon (C_Org) divided by a texture-based reference level was 1.12, 0.32 and 0.49 for natural forest, young and old agroforestry on very steep slopes, respectively. Within pine-based agroforestry relative decline with slope class (1–5) was pronounced in earthworms (biomass −3.46, population −4.18) and infiltration rates (−2.35) while bulk density increased (0.49); for soil carbon (C_Org), nitrogen, available phosphorus and exchangeable Mg effects in the −1.26 to −1.68 range indicated a loss of functional topsoil. Differences with age of the agroforestry systems were much smaller but included a decreasing earthworm population but an increase in mean earthworm weight and partial recovery of the C_Org/C_Ref ratio. Pine-based agroforestry on very steep soils had only 10%–14% of the earthworm biomass and 35% of the infiltration rate of reference natural forest. Understory vegetation biomass and litter layer necromass were more than five-fold higher in the natural forest. Across all samples a higher C_Org and higher earthworm biomass were associated with complementary positive changes in infiltration rates and soil porosity. Regression analysis suggests equal skill of tree cover, soil C_Org, porosity, aggregate stability and earthworms to predict infiltration rates while explanatory variables were strongly correlated. Management of the pine plantations may have to achieve a closer approximation of the conditions in natural forests to effectively protect upper watersheds. Full article

Understory community diversity in urban forests is crucial for maintaining urban ecosystem functions and enhancing urban resilience, but it is threatened by rapid urbanization. Currently, there remains a knowledge gap regarding the multi-scale responses and driving mechanisms of understory community diversity along urbanization gradients, which hinders its scientific conservation and management. This study was conducted in Shanghai, a highly urbanized metropolis in China, at both plot and site scales. A total of 75 plots and 380 quadrats were established across 16 urban forest sites. Five key environmental factors were selected, including distance from the city center, visitor intensity, non-native species richness, overstory coverage, and forest area. Using taxonomic and phylogenetic diversity, regression models and null models were employed to analyze the multi-scale patterns and underlying assembly processes of understory plant communities. The results showed that the effects of environmental factors were scale-dependent, with environmental filtering as the core assembly mechanism. At the plot scale, the distance from the city center exhibited a U-shaped relationship with species richness (p = 0.005), while visitor intensity displayed a unimodal pattern with both species richness (p < 0.001) and Faith’s phylogenetic diversity (PD, p = 0.029). Increased non-native species richness intensified phylogenetic clustering (p < 0.05), and environmental filtering was the dominant process of community assembly. At the site scale, the β-diversity of non-native species drove the increase in phylogenetic the β-diversity of understory communities (p < 0.001); geographical distance had a significant positive effect on βMNTD (p = 0.002); and differences in non-native species could weaken biotic homogenization (p < 0.05). This study clarifies the multi-scale response patterns and driving mechanisms of understory community diversity and structure, providing a scientific basis for optimizing the conservation and management of understory vegetation in urban forests and enhancing urban ecosystem stability. Future work calls for long-term monitoring and broader environmental indicators. Full article

Shade management, which is widely adopted in cultivation and understory regeneration, alters plant light environments, thereby degrading the trait inversion performance and posing a key challenge in plant phenotyping. To address this issue, this study reframed chlorophyll retrieval of Hopea hainanensis under shade management as an illumination-regime-dependent conditional domain shift problem, and developed a condition-aware domain adaptation framework (CAI-DAI) tailored to this setting. The results showed that chlorophyll content increased with shading intensity, accompanied by clear differences in canopy spectral distributions among shading levels, supporting the presence of condition-dependent variation under shade management. Model comparisons showed that CA-IE and CAI-DAI, which integrate conditional encoding and conditional alignment, performed better than the comparative models across fine-tuning ratios from 30% to 70%. Among them, CAI-DAI achieved the best and most stable performance, with test MAE ranging from 4.355 to 4.774 μg·cm⁻² and nRMSE ranging from 16.4% to 18.2%, and R² ranging from 0.456 to 0.585. Further evaluation at individual shading levels (S1–S4) showed that CAI-DAI produced narrower error ranges than CA-IE. It also showed smaller error fluctuations under most fine-tuning ratios. These results demonstrate that the proposed framework effectively improves robustness under heterogeneous shading conditions and limited labeled samples, providing methodological support for chlorophyll monitoring and decision-making related to shade management. Full article

Soil erosion in mountain environments is governed by the interaction of climatic drivers, surface conditions, and geomorphic connectivity. Recently, disturbance by large herbivores has been recognized as a potentially important but poorly quantified geomorphic driver. However, the combined effects of freeze–thaw processes and ungulate disturbance on sediment production remain unclear. This study provides quantitative field-based evidence linking deer activity to hillslope sediment flux in a montane forest catchment in central Japan. A six-year dataset (2019–2025), including climatic conditions, deer detections from camera traps, understory vegetation cover, and hillslope sediment flux (<9.5 mm) was analyzed. Multiple regression analysis was conducted using daily sediment flux as the response variable and maximum 1 h rainfall, freeze–thaw frequency, and daily deer detections as explanatory variables. The results showed that deer detections had a significant positive effect on sediment flux, whereas rainfall intensity and freeze–thaw frequency did not exhibit strong independent effects. Particle-size analysis further indicated that eroded sediment was markedly coarser than the surface soil, suggesting that short-term climatic drivers alone did not control sediment transport. These findings demonstrate that biotic disturbance by large herbivores can play a dominant role in hillslope sediment flux under cold, high-elevation conditions by modifying surface conditions and sediment connectivity. From a sustainability perspective, these results highlight the importance of managing deer populations to maintain ecosystem stability, prevent land degradation, and support sustainable forest and watershed management under changing environmental conditions. Full article

Cunninghamia lanceolata Lamb. occupies a significant role in artificial forests globally, making its sustainable management crucial for terrestrial forest ecology. We experimentally determined soil physicochemical properties and the shrub and herb diversity of different age classes of Cunninghamia lanceolata plantations in Southwest China in 2023. The Mantel tests, RDA, and PLS-SEM were used to analyze the effects of stand factors on soil fertility and shrub and herb diversity. Shrub and herb diversity, as well as soil physicochemical properties, vary significantly across age classes in Cunninghamia lanceolata plantations. The maximum values of organic carbon, total nitrogen, total phosphorus, and available silicon were observed in the mature forest (36.62 g/kg, 1.90 g/kg, 0.53 g/kg, and 84.33 mg/kg, respectively), while the minimum values were found in the middle-aged forest (17.77 g/kg, 0.81 g/kg, 0.34 g/kg, and 53.70 mg/kg). TPH was the most influential stand factor. TBH was strongly correlated with RDA1 (r = 0.821, p < 0.001); soil organic carbon, total nitrogen, total phosphorus, and available silicon were negatively correlated with stand density. In this study, we propose a detailed age class-based thinning plan with strong implementability: cultivating large-diameter timber, maintaining soil fertility and understory plant diversity, and being friendly to forest farm management personnel. This approach could enhance biodiversity and ecosystem stability in Cunninghamia lanceolata plantations and serves as a reference for the sustainable management and operation of the Cunninghamia lanceolata forest ecosystem. Full article

Understanding the drivers of understory vegetation diversity in plantation forests is critical for ecosystem management, yet traditional analytical methods are often constrained by assumptions of normality, linearity, and independence among variables. This study used the geographical detector (GeoDetector) method to quantify the independent and interactive effects of environmental factors on understory plant diversity in Pinus tabuliformis plantations. We established 36 standard plots at the Shihe Forest Farm in the Zhongtiao Mountains of Shanxi Province, China. A total of 25 environmental factors, encompassing stand structure, topography, soil physical properties, and soil chemical properties, were examined as potential drivers of shrub-layer and herb-layer diversity. The results identified distinct key drivers for different vegetation layers. Shrub-layer diversity was primarily influenced by regeneration potential, aspect, soil non-capillary porosity, and total soil nitrogen. In contrast, herb-layer diversity was mainly driven by forest type, slope, soil non-capillary porosity, and the soil nitrogen-to-phosphorus ratio. Factor interactions were widespread, with nonlinear enhancement and bivariate enhancement being the dominant types. The combined effect of interacting factors was consistently stronger than that of any single factor alone. Compared to conventional statistical methods, GeoDetector does not rely on linear assumptions and is unaffected by multicollinearity. This allows for more effective identification of drivers that have low independent explanatory power yet high ecological importance, as well as their interactive effects. This study demonstrates that vegetation diversity in P. tabuliformis plantations results from the synergistic effects of multiple factors. The findings provide a theoretical basis for managing and enhancing understory biodiversity in plantation ecosystems. Furthermore, they offer a novel and effective analytical framework for investigating the environmental driving mechanisms of understory vegetation diversity. Full article

The genus Juniperus species is widely distributed in the Northern Hemisphere of the planet Earth. These species are notable for their ability to adapt to extreme environmental conditions, playing a crucial role in ecosystem structure and function. Currently, their expansion is being driven by anthropogenic activities and climate change, posing significant challenges for both control and conservation. The objective of this review was to synthesize the available evidence regarding the ecological importance and impacts of Juniperus on ecosystems, promoting a holistic perspective that contributes to the achievement of the United Nations 2030 Agenda for Sustainable Development. A systematic literature search was conducted using the Scopus database, and only the documents published between 2001 and 2025 were considered for the investigation. The results showed that these species possess a high ecological versatility, favoring their invasive success in disturbed ecosystems, particularly under the influence of climate change and land-use changes. Conversely, Juniperus species facilitate positive ecological outcomes by providing essential ecosystem services that benefit both the human population and the flora and fauna present in these ecosystems. Nevertheless, their expansion also causes negative effects, such as the suppression of herbaceous shrubs and understory cover, alteration of the hydrological function, and accelerated soil erosion, among others. Consequently, the genus Juniperus exhibits a dual ecological role, acting as a hero to many species within these ecosystems, yet a villain to others. In this sense, given its remarkable adaptive dynamism under scenarios of climate change and continuous anthropogenic alterations, it is imperative to promote comprehensive conservation and restoration strategies. These should include ecological monitoring, invasive species control, genetic management, and habitat restoration. Such efforts must be supported by long-term interdisciplinary research to understand and mitigate the ecological, genetic, and social impacts resulting from its expansion. Furthermore, these investigations and strategies must be flexible and locally contextualized to promote genuine ecosystem resilience in the face of the ongoing environmental transformations. Full article

This study focuses on enhancing wind speed prediction for wildfire spread simulation by proposing an integrated forecasting approach. The original wind speed series is first processed via variational mode decomposition (VMD), with its parameters [K, $\alpha$] optimized via particle swarm optimization (PSO). Every intrinsic mode function (IMF) resulting from this decomposition is predicted using a bidirectional long short-term memory model incorporating an attention mechanism (AM-BiLSTM), and the final wind series is reconstructed from these predictions. Model training and validation were conducted using data from controlled burning experiments in the Mao’er Mountain area of Heilongjiang Province, China. Predictive performance is evaluated through multiple statistical metrics, error distribution analysis, and Taylor diagrams. To assess practical utility, the predicted wind field is further applied in FARSITE to drive wildfire spread simulations. Results demonstrate that the PSO-VMD-AM-BiLSTM model provides reliable wind forecasts and contributes to improved fire spread prediction accuracy, indicating its potential for decision support in wildfire management. To achieve accurate forest fire spread prediction, we construct the MCNN model, which is based on early perception of understory wind fields using predicted wind speed data and adopts a multi-branch convolutional neural network architecture to extract fire spread features. FARSITE is employed to simulate forest fire spread in the Mao’er Mountain region, generating a dataset for model training and testing. After 50 training epochs, the loss value of the MCNN model converges, achieving optimal prediction performance when the combustion threshold is set to 0.7. Compared to models such as CNN, DCIGN, and DNN, MCNN shows improvements in evaluation metrics including precision, recall, Sørensen coefficient, and Kappa coefficient. To validate the model’s predictive performance in real fire scenarios, four field ignition experiments were conducted at the Liutiao Village test site: homogeneous fuel combustion, long fire line combustion, alternating fuel combustion, and multiple ignition source merging combustion. Comprehensive evaluation across the four experiments indicates that the model achieves precision, recall, Sørensen coefficient, and Kappa coefficient values of 0.940, 0.965, 0.953, and 0.940, respectively, with stable prediction errors below 6%. These results represent improvements over the comparative models DCIGN and DNN. The proposed MCNN model can adapt to forest fire spread prediction under different scenarios, offering a novel approach for accurate forest fire prediction and prevention. Full article

Urban mental health burdens are increasing, prompting interest in how nearby green spaces aid emotional restoration. Bamboo-dominant green spaces are widespread in East Asia, but evidence connecting their management and structural features to restorative experiences is limited. This study conducted a controlled photo-exposure experiment in Ya’an, China, to examine how bamboo space typology and structural attributes relate to visual attention, affective responses, and short-term physiological recovery. One hundred and twenty participants viewed 50 photographs representing five bamboo space types (ecological conservation, productive–economic, protective–greenbelt, landscape–recreational, and understory–composite). Each image was linked to a matched field plot, enabling integration of structural indicators with eye tracking, EEG β/α, and repeated ratings of relaxation, pleasure, and preference. Results showed that landscape–recreational spaces received the highest affective ratings, while understory–composite spaces had longer fixations, indicating higher visual processing demands. Vertical stratification and groundcover coverage were robust predictors of affect beyond typology. Eye-movement metrics did not mediate structure–affect associations, and EEG β/α, as an auxiliary and context-dependent indicator under brief photo-based exposure, showed limited sensitivity. These findings offer insights into structural elements that can inform the design and management of bamboo green spaces for improved emotional restoration. Full article

The construction of photovoltaic (PV) power stations for sand control in northwestern China has exacerbated the conflict between solar resource utilization and ecosystem fragility, creating urgent ecological challenges that demand immediate solutions. This study investigated Amorpha fruticosa growing under fixed adjustable PV panels at the CGN DaLate Photovoltaic Leading Base in the eastern hinterland of the Kubuqi Desert. Through long-term field observations, three shading time gradients were established: heavy shading (HS), light shading (LS), and no shading (CK, control). The results clearly demonstrated that: (1) Plants in the LS treatment exhibited significantly greater plant height, basal diameter, and crown width compared to those in HS and CK, indicating optimal growth status and morphological plasticity. They maintained the highest net photosynthetic rate (Pn) and water use efficiency (WUE), while their intercellular CO₂ concentration (Ci) was significantly lower than in CK, effectively mitigating photosynthetic inhibition caused by high light intensity. Total chlorophyll (Chl) content increased significantly with increasing shading intensity, whereas the Chl a/b ratio decreased. (2) The LS treatment yielded the highest nitrogen (N), phosphorus (P), and crude protein (CP) contents, along with a more balanced N:P ratio, suggesting a superior state of nutritional metabolism. Growth indicators showed significant positive correlations with WUE and Chl content, and significant negative correlations with transpiration rate (Tr) and Ci, confirming a synergistic “physiological adaptation-growth optimization” mechanism. Our results demonstrate that light shading represents the optimal condition for the growth and biomass accumulation of A. fruticosa, highlighting its potential as a key species for vegetation restoration in PV power stations within arid ecosystems. These findings not only elucidate the plant’s adaptation mechanisms but also provide a crucial physiological basis for selecting and managing understory vegetation, thereby supporting the optimization of integrative “PV-Ecology” systems for sustainable desert restoration. Full article

White-tailed Deer (Odocoileus virginianus) overabundance has emerged as a significant ecological concern in recent decades. With current populations exceeding 30 million, White-tailed Deer (WTD) are now one of the most spatially abundant ungulate species across both natural and human-altered environments. High densities have led to considerable ecological and economic impacts, including forest understory degradation, biodiversity loss, and increased deer-vehicle collisions. This study examines the spatiotemporal distribution of WTD within three sites at Binghamton University, a heavily wooded campus in the Appalachian Upland region of New York State. To monitor population densities and movement patterns, a combination of remote sensing techniques was employed, including six Assark PH960W trail cameras and a DJI Mavic 3T UAV equipped with an uncooled VOx microbolometer thermal infrared (IR) sensor. Data were collected between 31 October 2024 and 10 March 2025, in relation to three deer culling events on 18 December 2024, 2 January 2025, and 9 January 2025. While Unoccupied Aerial Vehicle (UAV) based thermal imaging proved effective for estimating population dynamics, its utility is constrained by environmental and logistical limitations. In contrast, WiFi-enabled trail cameras provide a cost-efficient approach for capturing high-temporal resolution data at localized sites. Density estimates were derived from UAV thermal imaging and Random Encounter and Staying Time (REST) model calculations, ranging from 13.2 to 26.8 deer/km² across the region. Findings underscore the need for ongoing deer management strategies on campus to support long-term forest ecosystem health. Full article