Search Results (25)

Amidst global urbanization and rising psychological stress, urban green spaces are increasingly recognized as critical infrastructure for sustainable urban development and public health. However, the mechanisms by which summer vegetation structure mediates both physiological and psychological restoration, and the interplay between these two dimensions, remain poorly understood. Understanding these mechanisms is essential for designing sustainable, health-promoting urban environments that can support growing urban populations in a warming climate. This study employed a controlled field experiment in Xi’an during summer to examine the effects of five vegetation structure types (Single-Layer Grassland, single-layer woodland, tree–shrub–grass composite woodland, tree–grass composite woodland, and a non-vegetated square) on university students’ physiological (heart rate variability) and psychological (perceived restorativeness and affective states) restoration. Following stress induction, 300 participants engaged with the green spaces through both quiet sitting and walking. The results revealed three key findings: (1) the tree–shrub–grass composite woodland consistently showed the most favorable trends other vegetation types across all psychological restoration dimensions, while also showing favorable trends in physiological recovery, underscoring the importance of structural complexity for restorative quality; (2) walking significantly enhanced physiological recovery compared to seated observation across all settings, confirming the role of physical activity as a critical activator of green space benefits; (3) correlation analysis identified a specific cross-system association: the R-R interval recovery value showed a weak but significant correlation with positive affect (PA) scores, suggesting that physiological calmness and positive emotional experience are linked, yet their weak coupling under short-term exposure indicates they may operate as parallel processes with distinct temporal dynamics. These findings indicate that the restorative potential of summer green spaces emerges from an integrated framework combining vegetation complexity and activity support. We propose that future sustainable landscape design should prioritize multi-layered vegetation structures as nature-based solutions that simultaneously enhance human well-being and urban resilience. These findings provide empirical evidence for integrating health-promoting green infrastructure into sustainable urban planning frameworks, supporting multiple Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Full article

Roadside green spaces function as critical ecological barriers in urban environments, and their plant communities play a key role in improving regional air quality. This study investigates typical roadside plant communities in southern Xinjiang, a region characterized by extreme aridity and frequent dust storms. By quantifying indicators such as dust retention capacity at both individual and community levels, together with leaf surface microstructural characteristics, we evaluate the comprehensive dust retention performance of different community configuration patterns. The results show that: (1) Among the studied species, Juniperus chinensis ‘Kaizuca’ exhibited the highest dust retention capacity per unit leaf area, followed by Juniperus chinensis L. and Rosa rugosa Thunb. Among trees, Platanus acerifolia (Aiton) Willd showed the greatest dust retention capacity per individual plant; among shrubs, Rosa rugosa Thunb. performed strongly, and among herbaceous species, Lolium perenne L. exhibited relatively high dust retention capacity. (2) Leaf dust retention is governed by the synergistic effects of multiple traits, including leaf aspect ratio, stomatal aspect ratio, stomatal protrusion, stomatal density, wax layer characteristics, and surface roughness. Leaf aspect ratio exerts a significant positive direct effect on dust retention, whereas stomatal aspect ratio shows a significant negative direct effect. (3) At the community level, the multi-layered tree–shrub–herbaceous configuration dominated by Platanus acerifolia (Aiton) Willd exhibited the strongest dust retention capacity, making it the most effective configuration for roadside green spaces. Overall, this study provides a robust theoretical framework and empirical evidence for the scientific selection and optimized configuration of roadside vegetation in arid regions, thereby supporting the sustainable improvement of urban roadside air quality in southern Xinjiang. Full article

This study aimed to analyze changes in vegetation, built-up areas, and population growth in Lahore city from 1990 to 2023. The data was acquired from Google Earth Engine, and the spectral bands were retrieved from Landsat 5 and Landsat 8. The decadal analysis of the landscape was conducted from 1993 to 2001, 2001 to 2012, and from 2013 to 2023. Further analysis was conducted in ArcGIS version 10.3 to evaluate the Normalized Difference Vegetation Index and the Normalized Difference Built-up Index to assess vegetation and built-up areas, respectively. To analyze the urban population of Lahore, data were obtained from the Global Human Settlement Layer for 1990, 2000, 2010, and 2020. Results revealed that the total vegetated area of Lahore city decreased from 1453.0 km² in 1993–2001 to 788.2 km² in 2013–2023. Moreover, the urban built-up area expanded from 319.6 km² in 1993–2001 to 966.8 km² in 2013–2023. Sub-district-level analysis indicated that Model Town and Raiwind areas of Lahore depicted better vegetation recovery in this decade. The population of Lahore has been increasing steadily, with the 2010s being a particularly rapid period of growth. The projections for 2030 also depict a continuous growth pattern. This study was further developed by integrating multi-decadal averaging coupled with selected-year analysis to distinguish gradual land transformation from relatively accelerated phases of urban expansion of Lahore. Also, by combining NDVI and NDBI values on both Lahore and its tehsil level, the research provides a collective sub-district- and district-level perspective into the spatial heterogeneity of peri-urban transformations. The findings of the study explain how major infrastructural projects shape the urban growth patterns of cities like Lahore and cause a decline in the green areas of fast-growing cities in South Asia. This study further highlights the consequences of unplanned urban expansion in regions where high population growth has compromised green infrastructure and threatened ecological balance. In addition, it supports several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land) by providing spatial evidence of urban expansion of the city and losses of its green spaces. The findings offer empirical insights to support climate-resilient developments. The study also demonstrates the necessity of integrating green infrastructure and providing robust strategies for forthcoming urban planning projects and policy development regarding urban expansion. Full article

Decentralized graywater treatment using nature-based systems represents a sustainable, low-energy alternative to centralized wastewater technologies, particularly in water-scarce regions. This study evaluates the performance of a rain-garden-based constructed wetland implemented at Zain Park in Jerash, Jordan, for on-site graywater treatment and potential non-potable reuse. The system consists of two filtration beds with multi-layer gravel–sand media planted with ornamental vegetation to promote physical filtration, adsorption, and biologically mediated transformations. Influent and effluent samples were monitored monthly from April 2024 to January 2025 and analyzed for biodegradable and oxidizable organic fractions (BOD₅ and COD), nutrients (TN, PO₄³⁻), suspended solids, turbidity, salinity indicators, and microbial parameters (E. coli and total coliform). Average removal efficiencies reached 98% for BOD and 96% for COD, while turbidity and TSS were reduced by more than 96%, indicating effective organic degradation and particulate retention. Nutrient removal was moderate, with 40% reduction in Total Nitrogen and 74% in nitrate, reflecting partial nitrification–denitrification and plant uptake. Microbial removal was variable, with an average reduction of 0.8 log₁₀ (64.7%) for E. coli and 1.1 log₁₀ (82.6%) for total coliforms, indicating that passive filtration alone may not ensure complete pathogen attenuation. Post-treatment disinfection and substrate enhancements (aeration and plant selection) can strengthen system efficiency and support sustainable graywater reuse in water-stressed regions, contributing directly to SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), and SDG 12 (Responsible Consumption and Production). These findings support the applicability of compact constructed wetland systems as decentralized wastewater treatment solutions in arid and semi-arid urban environments. Full article

Landscape fragmentation as a process of landscape transformation affects the structure and composition of plant communities; however, relationships between fragmentation metrics and vegetation characteristics often remain weakly expressed and difficult to interpret, especially under conditions of multiple natural (wildfires, windstorms, pest outbreaks) and anthropogenic stressors (construction, forest management, agriculture). The aim of this study was to identify the sensitivity of forest community characteristics to landscape fragmentation metrics using methods that are effective at low correlation coefficients. The study analyzed 1694 vegetation relevés of forest communities in the center of the Russian Plain in the territory of the Moscow region. Seven uncorrelated metrics were calculated using the moving window method (2000 m) in Fragstats 4.3. The relationships between selected metrics and 20 community characteristics were evaluated using Spearman’s rank correlation method, assessment of statistically significant differences between classes, and testing for non-linear interactions. The species richness and Shannon index showed no correlation with fragmentation for tree and herb layers; however, the composition of ecological–coenotic groups demonstrated high sensitivity. The proportion of boreal and oligotrophic species, as well as the moss layer abundance, increased with increasing patch size, while nemoral and adventive species dominated in small-contrast patches. Results showed that fragmentation leads to asynchronous responses from ecosystem components, reducing correlations between structure and functioning. The conservation of large connected forest patches is critical for preserving the boreal–oligotrophic complex and moss layer, and is a priority task for climate adaptation. The robustness of the findings is supported by the extensive number of analyzed vegetation relevés. The multi-method approach demonstrated effectiveness in identifying significant ecological patterns under conditions of high multifactorial impact, emphasizing the need for a functionally oriented approach to managing fragmented temperate forests. Full article

The ecological strategies of understory shrubs are critical for maintaining the structure and function of forest understory vegetation. Understanding the assembly mechanisms of these shrub communities is a central issue in modern ecology. To address this, our study was conducted in the typical red soil regions of Jiangxi, China, focusing on secondary forests (including both broadleaved and coniferous types) of similar stand age. We aimed to assess the effects of various environmental factors—such as soil pH, total nitrogen content, bulk density, and understory temperature—along with tree-layer characteristics—including canopy closure, tree species richness, and diameter at breast height (DBH)—on the species composition, functional traits, and phylogenetic structure of the shrub layer. Results showed: One-way ANOVA revealed significant differences in functional traits between the two forest types. Specifically, leaf thickness, specific leaf area, and chlorophyll content were significantly higher in the coniferous forest, whereas leaf dry matter content was significantly lower compared to the broadleaved forest (p < 0.05). These results suggest that understory shrubs in the coniferous forest primarily adopt a resource-conservative strategy, while those in the broadleaved forest exhibit a resource-acquisitive strategy. Phylogenetic analysis further revealed that the phylogenetic diversity (PD) of coniferous forests was significantly lower than that of broadleaved forests (p < 0.05). The phylogenetic structure in coniferous forests showed a more clustered pattern (NTI > 0, NRI > 0), suggesting stronger environmental filtering. Diversity index analysis showed that the Chao1 index indicated a richer potential species pool in broadleaved forests (p < 0.05), while species distribution was more even in coniferous forests (p < 0.05). Random Forest model analysis identified the diameter at breast height (DBH) of trees as the most critical negative driver, while soil pH was the primary positive driver. Redundancy Analysis (RDA) confirmed that the community structure in coniferous forests was mainly driven by biotic competition pressure represented by DBH, whereas the structure in broadleaved forests was more closely associated with abiotic factors like soil total nitrogen and pH (R² = 0.29, p < 0.05). These environmental drivers, through strong environmental filtering, collectively resulted in a phylogenetically clustered pattern of shrub communities in both forest types. This study demonstrates that the assembly of understory shrub communities is a complex, multi-level process co-regulated by multiple factors, shaped by both the biotic pressure from the overstory structure and abiotic filtering from the soil environment. This finding deepens our understanding of the rules governing community assembly in forest ecosystems. Full article

Periphytic algae, as representative aquatic epiphytic communities, play a vital role in the material cycling and energy flow in rivers. Through physiological processes such as photosynthetic carbon fixation and nutrient absorption, they perform essential ecological functions in water self-purification, maintenance of primary productivity, and microhabitat formation. This study investigates the interaction mechanisms between these highly flexible organisms and the hydrodynamic environment, thereby addressing the limitations of traditional hydraulic theories developed for rigid vegetation. By incorporating the coupled effects of biological flexibility and water flow, an innovative nonlinear resistance model with velocity-dependent response is developed. Building upon this model, a coupled governing equation that integrates water flow dynamics, periphytic algae morphology, and layered Reynolds stress is formulated. An analytical solution for the vertical velocity distribution is subsequently derived using analytical methods. Through Particle Image Velocimetry (PIV) measurements conducted under varying flow velocity conditions in an experimental tank, followed by comprehensive error analysis, the accuracy and applicability of the model were verified. The results demonstrate strong agreement between predicted and measured values, with the coefficient of determination R² greater than 0.94, thereby highlighting the model’s predictive capacity in capturing flow velocity distributions influenced by periphytic algae. The findings provide theoretical support for advancing the understanding of ecological hydrodynamics and establish mechanical and theoretical foundations for river water environment management and vegetation restoration. Future research will build upon the established nonlinear resistance model to investigate the dynamic coupling mechanisms between multi-species periphytic algae communities and turbulence-induced pulsations, aiming to enhance the predictive modelling of biotic–hydrodynamic feedback processes in aquatic ecosystems. Full article

Forest management plans offer valuable data on forest species composition and structure, useful for large-scale bird conservation. We examined the relationship between bird community diversity and five vegetation characteristics from management plans in Krkonoše Mts. National Park. Bird communities were surveyed from 2012 to 2014 using the point method on 285 plots (radius 100 m). We analyzed songbirds, woodpeckers, and pigeons. The vegetation characteristics were divided into composition (tree species proportion, soil-based phytocoenosis, and target vegetation type) and structure (vertical tree layering and remotely sensed heights). Bird species richness was used as a diversity measure. Redundancy analysis (RDA) tested the impact of vegetation characteristics on bird community composition. Higher bird diversity was linked to deciduous forests, particularly beech, in multi-layered stands (20–40 m height) on rich soils. In contrast, lower diversity occurred in spruce-dominated stands with Scots pine, waterlogged soils, and low vegetation (<0.5 m). All vegetation characteristics correlated significantly with bird community diversity and composition. Our findings demonstrate that forest management data can help identify key variability sources in bird communities, aiding in large-scale monitoring and landscape planning. Beyond tree composition and structure, phytocoenological characteristics provide useful insights for conservation. Full article

Urban green spaces are critical yet understudied areas where anthropogenic and biological sounds interact. This study investigates how vegetation structure mediates the acoustic partitioning of urban soundscapes and informs sustainable forestry management. Through the principal component analysis (PCA) of 1–11 kHz frequency bands, we identified anthropogenic sounds (1–2 kHz) and biological sounds (2–11 kHz). Within bio-acoustic communities, PCA further revealed three positively correlated sub-clusters (2–4 kHz, 5–6 kHz, and 6–11 kHz), suggesting cooperative niche partitioning among avian, amphibian, and insect vocalizations. Linear mixed models highlighted vegetation’s dual role: mature tree stands (explaining 19.9% variance) and complex vertical structures (leaf-height diversity: 12.2%) significantly enhanced biological soundscapes (R²m = 0.43) while suppressing anthropogenic noise through canopy stratification (32.3% variance explained). Based on our findings, we suggest that an acoustic data-driven framework—comprising (1) the preservation of mature stands with multi-layered canopies to enhance bioacoustic resilience, (2) strategic planting of mid-story vegetation to disrupt low-frequency noise propagation, and (3) real-time soundscape monitoring to balance biophony and anthropophony allocation—can contribute to promoting sustainable urban forestry management. Full article

Air pollution poses a significant threat to human health, especially in urban areas. Urban parks function as natural biofilters, and examining the factors influencing dust retention—specifically PM2.5 and PM10 concentrations—across different spatial scales can enhance air quality and resident well-being. This study investigates the factors affecting dust retention in urban parks at both the site and vegetation community scales, focusing on Xi’an Expo Park. Through on-site measurements and a land use regression (LUR) model, the spatial and temporal distributions of PM2.5 and PM10 concentrations were analyzed. The indications of the findings are as follows. (1) The LUR model effectively predicts factors influencing PM2.5 and PM10 concentrations at the site scale, with adjusted R² values ranging from 0.482 to 0.888 for PM2.5 and 0.505 to 0.88 for PM10. Significant correlations were found between particulate matter concentrations and factors such as the distance from factories, sampling area size, distance from main roads, presence of green spaces, and extent of hard pavements. (2) At the plant community scale, half-closed (30%–70% canopy cover), single-layered green spaces demonstrated the superior regulation of PM2.5 and PM10 concentrations. Specifically, two vegetation structures—the half-closed single-layered mixed broadleaf-conifer woodland (H1M) and the half-closed single-layered broad-leaved woodland (H1B)—exhibited the highest dust-retention capacities. (3) PM2.5 and PM10 concentrations were highest in winter, followed by spring and autumn, with the lowest levels recorded in summer. Daily particulate matter concentrations peaked between 8:00 and 10:00 a.m. and gradually decreased, reaching a minimum between 4:00 and 6:00 p.m. The objective of this study is to evaluate the impact of urban green spaces on particulate matter (PM) concentrations across multiple scales. By identifying and synthesizing key indicators at these various scales, the research aims to develop effective design strategies for urban green spaces and offer a robust theoretical framework to support the creation of healthier cities. This multi-scale perspective deepens our understanding of how urban planning and landscape architecture can play a critical role in mitigating air pollution and promoting public health. Full article

The survival of relict Taxus wallichiana var. wallichiana (Yunnan yew) is threatened by overexploitation for its quality wood and medicinal properties, particularly for taxol extraction. Understanding the current status of its communities and populations is crucial for protecting existing natural forest resources. We established 53 vegetation plots in Yunnan, southwestern China, where T. wallichiana var. wallichiana is the primary dominant species. These plots were classified into four forest types. The forests were multi-stratified, with T. wallichiana var. wallichiana frequently dominating the subcanopy and shrub layer. Species diversity indices did not significantly differ among the four forest types. The age structure of T. wallichiana var. wallichiana exhibited a multi-modal pattern, with a maximum age of 1165 years. Growth was slow, with an average radial growth rate of 0.78 mm/year. Despite its strong sprouting ability, the species had a poor seedling/sapling bank and suffered from inadequate regeneration. Its seedlings/saplings are shade-intolerant. This study provides a scientific basis for effective conservation strategies, emphasizing the need for in situ regeneration to ensure the survival of T. wallichiana var. wallichiana and its contributions to biodiversity and ecosystem services. Full article

Sea level rise (SLR) attributed to the melting of ice caps and thermal expansion of seawater is of great global significance to vast populations of people residing along the world’s coastlines. The extent of SLR’s impact on physical coastal areas is determined by multiple factors such as geographical location, coastal structure, wetland vegetation and related oceanic changes. For coastal communities at risk of inundation and coastal erosion due to SLR, the modelling and projection of future sea levels can provide the information necessary to prepare and adapt to gradual sea level rise over several years. In the following study, a new model for predicting future sea levels is presented, which focusses on two tide gauge locations (Darwin and Milner Bay) in the Northern Territory (NT), Australia. Historical data from the Australian Bureau of Meteorology (BOM) from 1990 to 2022 are used for data training and prediction using artificial intelligence models and computation of mean sea level (MSL) linear projection. The study employs a new double data decomposition approach using Multivariate Variational Mode Decomposition (MVMD) and Successive Variational Mode Decomposition (SVMD) with dimensionality reduction techniques of Principal Component Analysis (PCA) for data modelling using four artificial intelligence models (Support Vector Regression (SVR), Adaptive Boosting Regressor (AdaBoost), Multilayer Perceptron (MLP), and Convolutional Neural Network–Bidirectional Gated Recurrent Unit (CNN-BiGRU). It proposes a deep learning hybrid CNN-BiGRU model for sea level prediction, which is benchmarked by SVR, AdaBoost, and MLP. MVMD-SVMD-CNN-BiGRU hybrid models achieved the highest performance values of 0.9979 (d), 0.996 (NS), 0.9409 (L); and 0.998 (d), 0.9959 (NS), 0.9413 (L) for Milner Bay and Darwin, respectively. It also attained the lowest error values of 0.1016 (RMSE), 0.0782 (MABE), 2.3699 (RRMSE), and 2.4123 (MAPE) for Darwin and 0.0248 (RMSE), 0.0189 (MABE), 1.9901 (RRMSE), and 1.7486 (MAPE) for Milner Bay. The mean sea level (MSL) trend analysis showed a rise of 6.1 ± 1.1 mm and 5.6 ± 1.5 mm for Darwin and Milner Bay, respectively, from 1990 to 2022. Full article

As global temperatures rise, flooding and storm surges caused by extreme weather threaten people’s safety and nations’ development. Nature-based Solutions (NBS) are practical actions to support resilience to reduce flood risk and are applied in many countries. As the NBS approach mentions, small check dams made of gabion and wood can retain runoff and temporarily create detention basins to reduce the magnitude of floods and provide additional water resources. However, previous dam suitability research emphasized the criteria selection and decision method evolution, which costs time on the complex calculation and does not fit the NBS small dams. This research aims to optimize the site selection workflow of small dams in vulnerable informal settlements by utilizing Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Evaluation (MCE). Several thematic layers, such as land use, river density, building distance, vegetation cover index, slope, and elevation factors, were chosen to identify the suitable area in Mataniko catchment, Honiara. More importantly, it provides a more efficient model builder that can be replicated in ArcGIS 10.8, which contributes to visualizing scenarios of the inundation area of small dams at different heights. As a result, this study tested up to 35 potential small dams with 2.5 and 5 m wall height in the flood-prone Vara Creek and selected nine small dams with 5 m height and 15 small dams at 2.5 m as the best locations according to the volume and area. Overall, it is an efficient tool for designers to communicate with different stakeholders and applies to other developing countries facing frequent floods. Moreover, it provides a prototype and evidence of NBS action to address the flood issue. Full article

Previous research on the relationship between edaphic factors and species diversity patterns has mostly focused on topsoil between 0 and 30 cm, with less attention paid to deeper layers where many plant root systems are concentrated. Since considering deeper edaphic layers might help to unravel the maintenance mechanisms of plant diversity, in the present study we explored the relationship between vegetation β-diversity and a comprehensive set of soil chemical attributes at different depths. Based on vegetation and soil data from subtropical broad-leaved forest plots in the Nanling Mountains, China, we analyzed the driving factors of β-diversity patterns of trees, shrubs, and herbs using multi-site generalized dissimilarity modeling (MS-GDM). We found that the species composition dissimilarity of trees, shrubs, and herbs layers in the study area was highly diversified and dominated by species turnover components. Topsoil chemical properties were the best explainers for the β-diversity of trees (52.5%), followed by herbs (40.3%) and shrubs (21.8%). With the increase of soil depth, especially for depth >60 cm, soil chemical elements gradually lost explanatory power. Regarding the β-diversity of trees, it was mainly affected by altitude and available nitrogen (AN), total iron (Fe), and nickel (Ni) content in the soil of 0–60 cm depth. Concerning shrubs, the best β-diversity explainers were altitude, geographical distance, and nutrient elements of the soil above 40 cm. The main factors driving the β-diversity of herbs were altitude, total boron (B), total cadmium (Cd), and total nickel (Ni) of 0–40 cm soil. Overall, our results suggest that the environmental filtration process driven by altitude and soil factors, and dispersal limitations represented by geographical distance, affected the β-diversity patterns of Nanling forest communities. Full article

As urbanization continues to accelerate, the urban heat island effects have become one of the most important issues affecting the urban environment and people’s living experience. Numerous studies have shown that urban parks and green spaces can effectively alleviate the problem of the urban heat island effect and provide cooling and humidifying effects. Vegetation communities are a fundamental part of urban parklands, and multi-layered vegetation communities are considered to have better cooling and humidifying effects. Previous studies have focused on comparative analyses between different cover types of vegetation communities but have not explored the differences in the cooling and humidifying effects of multi-layered vegetation communities of the same cover type. Therefore, the Olympic Forest Park in Beijing was selected as the subject of this study, and multi-layered vegetation-covered (tree-shrub-grass) with different degrees of densities and uncovered squares were selected for the control and comparison. The cooling and humidifying effects of multi-layered vegetation communities with different canopy densities at different times of the day through field measurements were studied, and the influencing factors for this were analyzed. The results show that the tree cover is the core factor affecting temperature; the degree of the canopy density of multi-layered vegetation communities is significantly and positively correlated with the intensity of cooling and humidification, and the cooling and humidifying effect of multi-layered vegetation communities increases as the degree of canopy density increases. The results of this study can provide some references for the planning and design of urban parks and green spaces. Full article