Search Results (504)

In order to precisely improve the quality of major tree species in northern China, near-natural differentiated management has been gradually introduced into forestry practice, aiming to optimize forest structure, enhance forest quality, and promote nutrient cycling and water conservation. As an essential element of forest ecosystems, soil microbes contribute to biodiversity preservation and nutrient turnover in soils. This study selected three typical forest types (Quercus acutissima forest, Pinus tabulaeformis forest, and Pinus tabulaeformis × Quercus mixed forest) that have been managed with target trees on Zhongtiao Mountain. Using 16S/ITS rRNA high-throughput sequencing, this study systematically assessed the influences of forest type and soil depth (0–60 cm) on the soil properties and microbial communities. The results showed that the fungal alpha diversity indices were the highest in Pinus tabulaeformis forest, which decreased with soil depth. Actinobacteriota exhibited the greatest relative abundance in mixed forest, whereas Ascomycota predominated in the Pinus tabulaeformis forest. The microbial co-occurrence network exhibited greater complexity compared to the pure forest. Microbial carbon and nitrogen cycling functions showed strong correlation with soil pH and nutrient levels. Symbiotrophs dominated the fungal community, and ectomycorrhizae were significantly abundant in mixed forests. pH is the dominant factor driving changes in microbial communities. In summary, the mixed forest improved soil nutrients, enhanced the complexity of microbial networks, and supported higher ectomycorrhizal abundance. These findings provide practical guidance for improving soil health and stability of forest ecosystems through near-natural management. Full article

The escalating threat of climate-driven wildfires, land abandonment, wildland–urban interface expansion, and inadequate forest management poses an existential challenge to Mediterranean oak ecosystems, for which traditional fire suppression has proven insufficient. This paper presents a combination of integrated fire management (IFM) and closer-to-nature forest management (CTNFM) in a representative mixed Pyrenean oak (Quercus pyrenaica) forest at Quinta da França (QF), in Portugal. It is structured around three main objectives designed to evaluate this pioneer integrated approach: (1) to describe the integration of IFM and CTNFM within an agro-silvo-pastoral landscape; (2) to qualitatively assess its ecological, operational, and socio-economic outcomes; and (3) to quantitatively evaluate the effectiveness of two key nature-based solutions (NbSs), that is, prescribed burning and planned grazing, in reducing wildfire risk and enhancing forest resilience and biodiversity. By strategically combining proactive fuel reduction with biodiversity-oriented silviculture, the QF case provides a replicable model for managing analogous Mediterranean forested areas facing similar risks. This integrated approach supports forest multifunctionality, advancing both prevention and adaptation goals, and directly contributes to the ambitious targets set by the European Union’s New Forest and Biodiversity Strategies for 2030, marking a significant step towards a more sustainable and fire-resilient future for such Mediterranean landscapes. Full article

Carbon (C) sequestration and nitrogen (N) and phosphorus (P) accumulation in urban forest green spaces are significant for global climate regulation and alleviating nutrient pollution. However, the effects of management and conservation practices across different urban forest vegetation types on soil C, N, and P contents and stoichiometric ratios remain largely unexplored. We selected forest soils from Guangzhou, a major Metropolis in China, as our study area. Soil samples were collected from two urban secondary forests that naturally regenerated after disturbance (108 samples) and six urban forest parks primarily composed of artificially planted woody plant communities (72 samples). We employed mixed linear models and variance partitioning to analyze and compare soil C, N, and P contents and their stoichiometry and its main driving factors beneath suburban forests and urban park vegetation. These results exhibited that soil pH and bulk density in urban parks were higher than those in suburban forests, whereas soil water content, maximum storage capacity, and capillary porosity were higher in urban forests than in urban parks. Soil C, N, and P contents and their stoichiometry (except for N:P ratio) were significantly higher in suburban forests than in urban parks. Multiple analyzes showed that soil pH had the most pronounced negative influence on soil C, N, C:N, C:P, and N:P, but the strongest positive influence on soil P in urban parks. Soil water content had the strongest positive effect on soil C, N, P, C:N, and C:P, while soil N:P was primarily influenced by the positive effect of soil non-capillary porosity in suburban forests. Overall, our study emphasizes that suburban forests outperform urban parks in terms of carbon and nutrient accumulation, and urban green space management should focus particularly on the impact of soil pH and moisture content on soil C, N, and P contents and their stoichiometry. Full article

To explore the characteristics of species diversity and phylogenetic diversity, as well as the dominant processes of community construction, in different forest types (deciduous broad-leaved forest, mixed coniferous and broad-leaved forest, and Chinese fir plantation) in subtropical regions, analyze the specific driving patterns of soil nutrients and other environmental factors on the formation of forest diversity in different forest types, and clarify the differences in response to environmental heterogeneity between natural forests and plantation forests. Based on 48 fixed monitoring plots of 50 m × 50 m in Shouchang Forest Farm, Jiande City, Zhejiang Province, woody plants with a diameter at breast height ≥5 cm were investigated. Species diversity indices (Margalef index, Shannon–Wiener index, Simpson index, and Pielou index), phylogenetic structure index (PD), and environmental factors were used to analyze the relationship between diversity characteristics and environmental factors through variance analysis, correlation analysis, and generalized linear models. Phylogenetic structural indices (NRI and NTI) were used, combined with a random zero model, to explore the mechanisms of community construction in different forest types. Research has found that (1) the deciduous broad-leaved forest had the highest species diversity (Margalef index of 4.121 ± 1.425) and phylogenetic diversity (PD index of 21.265 ± 7.796), significantly higher than the mixed coniferous and broad-leaved forest and the Chinese fir plantation (p < 0.05); (2) there is a significant positive correlation between species richness and phylogenetic diversity, with the best fit being AIC = 70.5636 and R² = 0.9419 in broad-leaved forests; however, the contribution of evenness is limited; (3) the specific effects of soil factors on different forest types: available phosphorus (AP) is negatively correlated with the diversity of deciduous broad-leaved forests (p < 0.05), total phosphorus (TP) promotes the diversity of coniferous and broad-leaved mixed forests, while the diversity of Chinese fir plantations is significantly negatively correlated with total nitrogen (TN); (4) the phylogenetic structure of three different forest types shows a divergent pattern in deciduous broad-leaved forests, indicating that competition and exclusion dominate the construction of deciduous broad-leaved forests; the aggregation mode of Chinese fir plantation indicates that environmental filtering dominates the construction of Chinese fir plantation; the mixed coniferous and broad-leaved forest is a transitional model, indicating that the mixed coniferous and broad-leaved forest is influenced by both stochastic processes and ecological niche processes. In different forest types in subtropical regions, the species and phylogenetic diversity of broad-leaved forests is significantly higher than in other forest types. The impact of soil nutrients on the diversity of different forest types varies, and the characteristics of community construction in different forest types are also different. This indicates the importance of protecting the original vegetation and provides a scientific basis for improving the ecological function of artificial forest ecosystems through structural adjustment. The research results have important practical guidance value for sustainable forest management and biodiversity conservation in the region. Full article

Stem radius growth (GRO), tree water deficit (TWD), and maximum daily shrinkage (MDS) were monitored throughout 2023 in a semi-arid Mediterranean forest stand in Burdur, Türkiye, where Pinus nigra subsp. pallasiana (Lamb.) Holmboe and Pinus brutia Ten. naturally co-occur. These indicators, derived from electronic band dendrometers, were analyzed in relation to key climatic variables. Results indicated that P. brutia had a longer growth period, while P. nigra exhibited a higher average daily increment under the environmental conditions of 2023 at the study site. Annual stem growth was nearly equal for both species. Based on dendrometer observations, P. brutia exhibited lower normalized TWD and higher normalized MDS values under varying vapor pressure deficit (VPD) and soil water potential (SWP) conditions. A linear mixed-effects model further confirmed that P. brutia consistently maintained lower TWD than P. nigra across a wide climatic range, suggesting a comparatively lower degree of drought-induced water stress. GRO was most influenced by air temperature and VPD, and negatively by SWP. TWD was strongly affected by both VPD and SWP, while MDS was primarily linked to minimum air temperature and VPD. Moreover, MDS in P. brutia appeared more sensitive to climate variability compared to P. nigra. Although drought limited stem growth in both species during the study year, the lower TWD and higher MDS observed in P. brutia may indicate distinct physiological strategies for coping with drought. These findings offer preliminary insights into interspecific differences in water regulation under the particular climatic conditions observed during the study year in this semi-arid Mediterranean ecosystem. Full article

Climate change has intensified over recent decades, prompting shifts in forest management strategies, particularly in the Sudetes region of Poland, where native species like Norway spruce (Picea abies), European beech (Fagus sylvatica), and silver fir (Abies alba) have historically dominated. To address these changes, non-native species such as Douglas fir (Pseudotsuga menziesii) have been introduced as potential alternatives. This study, conducted in the Jugów and Świerki forest districts, compared the soil properties and water retention capacities of Douglas fir (Dg) and Norway spruce (Sw) stands (age classes from 8–127 years) in the Fresh Mountain Mixed Forest Site habitat. Field measurements included temperature, humidity, organic matter content, water capacity, and granulometric composition. Results indicate that, in comparison to Sw stands, Dg stands were consistently linked to soils that were naturally finer textured. The observed hydrological changes were mostly supported by these textural differences: In all investigated circumstances, Dg soils demonstrated greater water retention, displaying a water capacity that was around 5% higher. In addition to texture, Dg stands showed reduced soil water repellency and a substantially greater organic matter content (59.74% compared to 27.91% in Sw), which further enhanced soil structure and moisture retention. Conversely, with increasing climatic stress, Sw soils, with coarser textures and less organic matter, showed decreased water retention. The study highlights the importance of species selection in sustainable forest management, especially under climate change. Future research should explore long-term ecological impacts, including effects on microbial communities, nutrient cycling, and biodiversity, to optimize forest resilience and sustainability. Full article

Accurate estimation of aboveground biomass (AGB) in tree–shrub communities is critical for quantifying forest ecosystem productivity and carbon sequestration potential. Although generalized allometric equations offer expediency in natural forest AGB estimation, their neglect of interspecific variability introduces methodological pitfalls. Precise AGB prediction necessitates resolving two biological constraints: phylogenetic conservation of allometric coefficients and ontogenetic regulation of scaling relationships. This study establishes an integrated framework combining the following: (1) phylogenetic signal detection (Blomberg’s K/Pagel’s λ) across 157 species’ allometric equations, revealing weak but significant evolutionary constraints (λ = 0.1249, p = 0.0027; K ≈ 0, p = 0.621); (2) hierarchical error decomposition of 9105 stems in a Mt. Wuyishan forest dynamics plot (15 species), identifying family-level error stratification (e.g., Theaceae vs. Myrtaceae, Δerror > 25%); (3) ontogenetic trajectory analysis of Castanopsis eyrei between Mt. Wuyishan and Mt. Huangshan, demonstrating significant biomass deviations in small trees (5–15 cm DBH, p < 0.05). Key findings resolve the following hypotheses: (1) absence of strong phylogenetic signals validates generalized models for phylogenetically diverse communities; (2) ontogenetic regulation dominates error magnitude, particularly in early developmental stages; (3) differential modeling is recommended: species-specific equations for pure forests/seedlings vs. generalized equations for mixed mature forests. This work establishes an error hierarchy: ontogeny > taxonomy > phylogeny, providing a mechanistic basis for optimizing forest carbon stock assessments. Full article

Accurate estimation of forest aboveground biomass (AGB) and understanding its ecological drivers are vital for carbon monitoring and sustainable forest management. However, AGB estimation using remote sensing is hindered by signal saturation in high-biomass areas and insufficient attention to ecological structural factors. Focusing on Guangdong Province, this study proposes a novel approach that spatially extrapolates airborne LiDAR-derived Forest structural parameters and integrates them with Sentinel-1/2 data to construct an AGB prediction model. Results show that incorporating structural parameters significantly reduces saturation effects, improving prediction accuracy and AGB maximum range in high-AGB regions (R² from 0.724 to 0.811; RMSE = 10.64 Mg/ha; max AGB > 180 Mg/ha). Using multi-scale geographically weighted regression (MGWR), we further examined the spatial influence of forest type, age structure, and species mixture. Forest age showed a strong positive correlation with AGB in over 95% of the area, particularly in mountainous and hilly regions (coefficients up to 1.23). Species mixture had positive effects in 87.7% of the region, especially in the north and parts of the south. Natural forests consistently exhibited higher AGB than plantations, with differences amplifying at later successional stages. Highly mixed natural forests showed faster biomass accumulation and higher steady-state AGB, highlighting the regulatory role of structural complexity and successional maturity. This study not only mitigates remote sensing saturation issues but also deepens understanding of spatial and ecological drivers of AGB, offering theoretical and technical support for targeted carbon stock assessment and forest management strategies. Full article

Kazakhstan is recognized as one of the primary centers of origin of the wild apple Malus sieversii, concentrated mainly in the mountains like Trans-Ile and Zhongar Alatau, as well as parts of the Tarbagatay, Talas Alatau, and Karatau ranges. As the wild progenitor of Malus domestica, M. sieversii harbors a critical genetic diversity essential for apple breeding and conservation efforts. However, its natural populations are increasingly threatened by latent viral infection, which weakens trees, reduces reproduction, and hinders regeneration. In this study, the spread of apple chlorotic leaf spot virus (ACLSV) and apple stem pitting virus (ASPV) was documented in four wild apple populations, with detection rates of 50.2% and 42.2%, respectively. Mixed infections were observed in 28.8% of sampled trees. Apple stem grooving virus (ASGV) was detected exclusively in cultivated orchards, whereas apple mosaic virus (ApMV) and apple necrotic mosaic virus (ApNMV) were not found in either wild forests or cultivated orchards. Using Geographic Information System (GIS) technology, we developed the first spatial distribution maps of these viruses in wild apple forests in the Tian Shan region, revealing site-specific variation and infection rates. These results underscore the importance of monitoring viral infections in wild M. sieversii populations to preserve genetically valuable, virus-free germplasm critical for apple breeding, crop improvement, and sustainable orchard management. Full article

The Mixed Ombrophyllous Forest (MOF), inserted in the Atlantic Forest biome, is of great ecological value, with deficient management strategies. In this context, sustainable management helps to promote the regeneration and growth of individual trees and control others, while maintaining the natural forest structure. This study therefore aimed to discuss opportunities and limitations of biochar, produced from two species from the MOF, which are currently only utilized to a limited extent in the study area in southern Brazil. A slow pyrolysis process at a lab scale was designed, biochar was produced, and key properties were analyzed from Hovenia dulcis Thunb. (chosen as an invasive species) and Mimosa scabrella Benth. (chosen as a native, fast-growing species), including branches and stems. The results showed that branches of Mimosa scabrella (BMS) had the highest biochar yield (30.32 ± 0.3%) and the highest electrical conductivity (415.08 ± 24.75 mS cm⁻¹). Stems of Mimosa scabrella (SMS) showed the highest higher heating value (HHV—31.76 ± 0.01 MJ kg⁻¹), lower heating value (LHV—31.03 ± 0.01 MJ kg⁻¹), and energy yield (49.1%), while the branches of Hovenia dulcis (BHD) showed the lowest values. For the elemental analysis, SMS showed the best results, with the highest amount of fixed carbon (78.62 ± 0.22%) and carbon content (85.87 ± 0.083%), and consequently the lowest amount of ash (3.52 ± 0.08%). BHD showed a better water-holding capacity (303.26 ± 15.21%) and higher pH value (7.65 ± 0.14). The investigations conducted on the biochar from both species indicate a strong suitability of these woods for producing high-quality biochar. Full article

Cantabrian mixed forests, located in areas of Spain, Portugal, and France, serve as an essential biogeographic transition region, noted for its extraordinary plant diversity and ecological intricacy. To aid conservation and research initiatives, a uniform checklist of vascular plants was created, incorporating information from citizen science platforms, scientific databases, herbarium records, and local floras. The outcome is a carefully selected collection of more than 8000 taxa, with over 76% recognized as native, highlighting the area’s importance as a reservoir of biodiversity and a climate refuge. Taxonomic discrepancies were resolved via expert verification and adherence to international naming standards, establishing a dependable basis for ecological research. The checklist demonstrates notable variations in organisms, ecological approaches, and evolutionary lineages, influenced by geographical diversity, climate variations, and past land use patterns. Importantly, the study emphasizes the drawbacks of unchecked biodiversity data and shows the benefits of expert-driven synthesis for addressing gaps and biases in species documentation. The floristic information presented here can act as a basis for transboundary conservation planning, ongoing biodiversity tracking, and the development of adaptive management approaches in response to climate change and ecological decline. This initiative represents an important move towards safeguarding the distinct natural heritage of this distinctive biogeographic region. Full article

Earthquakes are sudden-onset disasters requiring rapid, accurate information for effective crisis response. Social media (SM) platforms provide abundant geospatial data but are often unstructured and produced by diverse users, posing challenges in filtering relevant content. Traditional content filtering methods rely on natural language processing (NLP), which underperforms with mixed-language posts or less widely spoken languages. Moreover, these approaches often neglect the spatial proximity of users to the event, a crucial factor in determining relevance during disasters. This study proposes an NLP-free model that assesses the spatial credibility of SM content by analysing users’ spatial trajectories. Using earthquake-related tweets, we developed a machine learning-based classification model that categorises posts as directly relevant, indirectly relevant, or irrelevant. The Random Forest model achieved the highest overall classification accuracy of 89%, while the k-NN model performed best for detecting directly relevant content, with an accuracy of 63%. Although promising overall, the classification accuracy for the directly relevant category indicates room for improvement. Our findings highlight the value of spatial analysis in enhancing the reliability of SM data (SMD) during crisis events. By bypassing textual analysis, this framework supports relevance classification based solely on geospatial behaviour, offering a novel method for evaluating content trustworthiness. This spatial approach can complement existing crisis informatics tools and be extended to other disaster types and event-based applications. Full article

Accurate modeling of height–diameter (h–d) relationships is critical for forest inventory and management, particularly in complex forest ecosystems such as natural and pure Crimean juniper (Juniperus excelsa Bieb.) stands. This study evaluates both traditional parametric and modern machine learning (ML) approaches to develop reliable h–d models based on 2135 sample trees measured in southern Türkiye. The modeling approaches include fixed-effects (FE), mixed-effects (ME), three quantile regression (QR) models based on three, five, and nine quantile levels, and non-parametric ML methods: shallow multilayer perceptron (S_MLP), extreme gradient boost (XGBoost), and random forest (RF). According to the assessment metrics for the fitting and test datasets, the XGBoost modeling approach achieved the most accurate performance. For the fitting dataset, it achieved root mean square error values of 1.11 m and 1.21 m. For the test dataset, the corresponding error values were 1.16 m and 1.24 m, resulting in the highest accuracy among all models, closely followed by the RF and S_MLP models. A key practical advantage of ML approaches is that they do not depend on calibration scenarios, meaning they can operate without the need for preliminary parameter configuration. In contrast, the ME model showed the highest accuracy among the parametric methods when calibration was applied. In this case, when applying ME models, the study recommends calibrating the model by measuring four randomly selected trees per plot to balance prediction accuracy and field sampling effort. Full article

Background: Physical and mental health issues are increasingly becoming a global focus of attention, and telemedicine is widely attracting academic interest. Objectives: This exploratory study aimed to investigate the therapeutic potential of immersive virtual blue spaces for individuals with distinct lifestyle backgrounds—specifically, office workers and retirees. The research explores how different virtual waterscapes influence emotional and physiological states in populations with varying stress profiles and life rhythms. Methods: A mixed-methods design was employed, combining quantitative measurements with qualitative interviews. In September 2023, forty participants (20 office workers and 20 retirees) from Hualien, Taiwan, were exposed to 360° VR simulations of three blue environments: a forest stream, a forest waterfall, and a beach scene. Pre- and post-session assessments included physiological indicators (blood pressure and heart rate) and emotional states measured using the Profile of Mood States (POMS) scale. Results: Significant physiological relaxation was observed among retirees. Office workers demonstrated greater emotional improvements, with noticeable variation depending on the type of virtual environment. Comparative analysis highlighted the stream landscape’s unique benefit for reducing depression and enhancing positive mood states. Thematic findings from post-session interviews further indicated that emotional responses were moderated by individual background and prior emotional experiences. Conclusions: These findings underscore the short-term therapeutic potential of virtual blue spaces for diverse user groups and reveal the influence of personal context on their effectiveness. The study supports the integration of VR-based nature exposure into personalized digital healthcare interventions and offers a foundation for future development in immersive therapeutic technologies. Full article

Forests in the Tolna region (Hungary) are distributed at the xeric limit of broadleaved forest zones and adapted to the arid ecological conditions of the wood-steppe climate. An 85-year-old in situ gene conservation stand of Quercus virgiliana mixed with other taxa of section Quercus was studied, which was regenerated naturally by both seedlings and coppicing. To analyze the phenotypes growing within the stand and the genetic structure of the population, a total of 138 trees were sampled. For taxonomic classification, a complex of morphological traits of oak taxa growing naturally in the region was used. Out of the 12 morphotype groups, only a few trees were classified as Q. virgiliana (eight individuals) or Q. robur (nine individuals), and the majority of the trees (121 individuals) were hybrid or introgressed phenotypes of Q. virgiliana adapted to xeric conditions by its xeromorphic traits. Despite the high number of coppiced trees (89 pcs vegetatively regenerated), the genetic variation was relatively high based on 16 nSSR markers used for analyses. Some of the trees were classified as non-autochthonous with Slavonian oak origin, both by morphological traits and SSR structure. Despite some alleles being lost, the allelic diversity of the seedling trees’ group was similar to that of the group of parent generation (coppiced trees). The spatial structure of trees supported the results of morphologic classification, and Q. virgiliana and hybrid phenotypes were growing on xeric microhabitats of the stand, mostly on southeast-facing slopes or ridges of hills. Consequently, the stand might fulfill all the in situ gene conservation requirements based on the high genetic diversity measured and the high number of xeromorphic phenotypes in the context of climate change as well. Full article