Search Results (199)

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

Coastal wetlands play important environmental roles. However, their hydrogeomorphological dynamics remain poorly understood under scenarios of extreme climate events. The aim of this study was to characterize the temporal and spatial variability of hydrogeomorphological attributes (vegetation, water, and soil) in the wetlands of Lagoa do Peixe National Park, Brazil. The methodology involved applying Principal Component Analysis (PCA) in both temporal (T) and spatial (S) modes, decomposing spectral indices for each attribute to identify variability patterns. The results revealed that vegetation and water are strongly correlated with seasonal dynamics influenced by ENSO (El Niño/La Niña) events. Soils reflected their textural characteristics, with a distinct temporal response to the water balance. PCA proved to be a useful tool for synthesizing large volumes of multitemporal data and detecting dominant variability patterns. It highlighted the Lagoon Terraces and the Lagoon Fringe, where low slopes amplified hydrological variations. Temporal variability was more responsive to climate extremes, with implications for ecosystem conservation, while spatial variability was modulated by geomorphology. Full article

In water-scarce regions, natural ecosystems and agriculture increasingly compete for limited water resources, intensifying stress during periods of drought. To assess these competing demands, we applied a modified PT-JPL model that incorporates the thermal inertial approach as a substitute for relative humidity (RH) in estimating soil evaporation—a method that significantly outperforms the original PT-JPL formulation in Mediterranean semi-arid irrigated areas. This remote sensing framework enabled us to quantify spatial and temporal variations in water use across both natural and agricultural systems within the UNESCO World Heritage site of Doñana. Our analysis revealed an increasing evapotranspiration (ET) trend in intensified agricultural areas and rice fields surrounding the National Park (R = 0.3), contrasted by a strong negative ET trend in wetlands (R < −0.5). These opposing patterns suggest a growing diversion of water toward irrigation at the expense of natural ecosystems. The impact was especially marked during droughts, such as the 2011–2016 period, when precipitation declined by 16%. In wetlands, ET was significantly correlated with precipitation (R > 0.4), highlighting their vulnerability to reduced water inputs. These findings offer crucial insights to support sustainable water management strategies that balance agricultural productivity with the preservation of ecologically valuable systems under mounting climatic and anthropogenic pressures typical of semi-arid Mediterranean environments. Full article

Evaluating the environmental perception of urban parks is highly significant for optimizing urban planning. To address the limitations of traditional evaluation methods, a multimodal deep learning framework that integrates pre-training and reinforcement learning strategies for the comprehensive assessment of various park types (seaside, urban, mountain, and wetland) across three dimensions—accessibility, usability, and aesthetics—is proposed herein. By combining image data and user review texts, a unified architecture is constructed, including a text encoder, image visual encoder, and multimodal fusion module. During the pre-training phase, the model captured latent features in images and texts through a self-supervised learning strategy. In the subsequent training phase, a reinforcement learning strategy was introduced to optimize the sample selection and modal fusion paths to enhance the model’s generalization capability. To validate the cross-type prediction ability of the model, the experimental design uses data from three types of parks for training, with the remaining type as a test set. Results demonstrate that the proposed method outperforms LSTM and CNN architectures across accuracy, precision, recall, and F1 Score metrics. Compared with CNN, the proposed method improves accuracy by 5.1% and F1 Score by 6.6%. Further analysis shows that pre-training enhances the robust fusion of visual and textual features, while reinforcement learning optimizes the sample selection and feature fusion strategies during training. Full article

Our study aims to analyze the spatiotemporal dynamics of six lakes in Ifrane National Park (Morocco) using remote sensing and satellite imagery over the period 2000–2024. Spectral indices such as NDWI, MNDWI, EWI, AWEI, and ANDWI were employed to extract water bodies from Landsat images, while the NDVI index was used to identify irrigated agricultural lands. Additionally, the SPEI and RDI indices were applied to assess the impact of climate fluctuations on the hydrological evolution of the lakes. The results reveal an alarming reduction in lake surface areas, with some lakes having completely dried up. This decline is correlated with decreased precipitation and the expansion of irrigated agricultural lands, highlighting the impact of human activities. The analysis of hydrological correlations between lakes demonstrates significant interactions, although some indices show disparities. The rapid expansion of agricultural land, particularly arboriculture, increases pressure on water resources. These changes threaten local biodiversity and heighten the socio-economic vulnerability of surrounding populations. Full article

The increasing development of coal mining subsidence wetland parks has led to a growing focus on assessing their ecological, economic, and social benefits following ecological restoration. This study establishes an assessment framework for the social landscape performance of coal mining subsidence wetland parks based on the landscape performance series (LPS), cultural ecosystem services (CES), and the unique characteristics of coal mining subsidence wetland parks. The framework integrates expert opinions and field research to select indicators, resulting in a comprehensive evaluation system comprising 28 indicators across five dimensions. Taking the Pan’an Lake National Wetland Park (PLNWP) in Xuzhou, China, as an example, we conducted empirical research by collecting data through questionnaires and on-site interviews. Using the fuzzy comprehensive evaluation method, the social landscape performance score of PLNWP was 3.511, which is rated as “good.” The importance–performance analysis (IPA) was applied to identify differences in the perceptions of visitors and local residents regarding the social landscape performance of the PLNWP. Local residents highlighted the need to enhance the amenity of waterside spaces, while visitors focused on the accessibility. Finally, based on the performance score and the perceptions from different stakeholders, optimization strategies were proposed in four aspects: enhancing waterside space amenity, optimizing accessibility, improving educational facilities, and addressing diverse user needs. This study could provide a feasible assessment framework and optimization guidance for other coal mining subsidence wetland parks. Full article

International industrial transfer has driven rapid construction land expansion in emerging metropolitan areas, posing challenges for sustainable land management. However, existing research has largely overlooked the spatiotemporal patterns and driving mechanisms of this expansion, particularly in Southeast Asian metropolitan regions. To address this gap, we focused on the Ho Chi Minh City metropolitan area, utilizing construction land data from GLC_FCS30D to analyze the dynamics of construction land expansion during this period. Findings indicated that: (1) Continuous expansion of construction land, with the expansion rate during 2010–2020 being five times that of 2000–2010; (2) The spatial pattern evolved from initial infilling development in urban cores to subsequent leapfrogging and edge expansion toward peripheral counties and transportation corridors; (3) The expansion of construction land occurred alongside substantial losses of wetland and cultivated land. Between 2000 and 2020, the conversion of cultivated land to construction land increased significantly, particularly during 2010–2020 when cultivated land conversion accounted for 93.76% of newly developed construction land. Wetland conversion also showed notable growth during this period, comprising 3.86% of total newly added construction land; (4) Foreign direct investment (FDI) served as the primary catalyst, while industrial park development and transport infrastructure projects functioned as secondary accelerants. This study constructed a framework to systematically analyze the global and local driving mechanisms of metropolitan land expansion. The findings deepen the understanding of land-use transitions in emerging countries and provide both theoretical support and policy references for sustainable land management. Full article

As one of Europe’s rare floodplain forest ecosystems, the İğneada Longos Forests face increasing ecological pressures; this study examines land use and land cover (LULC) changes in the İğneada Longos Forests, a protected national park in Turkey, between 1984 and 2014, while also assessing future climate change impacts under different shared socioeconomic pathways (SSPs). In this context, the MaxEnt model, which exhibits a very high sensitivity, was used to determine the land use/land change and the change in natural distribution habitats of the forest tree species in the İğneada Longos Forests, which constitute the research area, due to the effects of climate change. The analysis of forest management plans revealed significant LULC shifts, including wetland loss, cropland expansion, and declines in pioneer tree species, such as the lowland maple and the European ash, due to anthropogenic pressures and increasing droughts. Climate modeling using the Emberger and De Martonne indices projected severe aridity by 2100, with Mediterranean climate dominance expanding (up to 89.25% under SSP3–7.0) and humid zones disappearing. These changes threaten biodiversity, carbon sequestration capacity, and ecosystem stability, particularly in floodplain forests, which are critical for carbon storage. The findings underscore the urgent need for adaptive conservation strategies, stakeholder collaboration, and climate-resilient forest management to mitigate ecological degradation and sustain ecosystem services under escalating climate stress. Full article

Lack of green spaces, citizen insecurity, and crime are the primary issues afflicting the Pueblo Libre district. This research aims to propose public spaces that revalue the cultural and historical landscape of Pueblo Libre. The methodology involves a literature review, urban analysis, and climate analysis, incorporating sustainability strategies supported by digital tools (AutoCAD, Revit, and Sketch-Up). The resulting design features an ecological park with vegetation capable of capturing carbon and emitting oxygen, absorbing up to 3544.99 kg of CO₂ annually. It also includes installing 26 solar-powered lights to illuminate necessary spaces efficiently and using eco-friendly materials. Additionally, the park incorporates an artificial wetland with a capacity to process 38,500 L of water using plants that remove toxic elements and capture nutrients. In conclusion, the ecological park seeks to revalue the cultural landscape and counteract environmental degradation by creating a green lung that purifies the air, fosters social connectivity, and integrates users with nature, enhancing their quality of life. Full article

Urban planners are progressively recognizing the significant effects of the built environment and land use on PM_2.5 levels. However, in analyzing the drivers of PM_2.5 levels, researchers’ reliance on annual mean and seasonal means may overlook the monthly variations in PM_2.5 levels, potentially impeding accurate predictions during periods of high pollution. This study focuses on the area within the Sixth Ring Road of Beijing, China. It utilizes gridded monthly and annual mean PM_2.5 data from 2019 as the dependent variable. The research selects 33 independent variables from the perspectives of the built environment and land use. The Extreme Gradient Boosting (XGBoost) method is employed to reveal the driving impacts of the built environment and land use on PM_2.5 levels. To enhance the model accuracy and address the randomness in the division of training and testing sets, we conducted twenty comparisons for each month. We employed Shapley Additive Explanations (SHAP) and Partial Dependence Plots (PDP) to interpret the models’ results and analyze the interactions between the explanatory variables. The results indicate that models incorporating both the built environment and land use outperformed those that considered only a single aspect. Notably, in the test set for April, the R² value reached up to 0.78. Specifically, the fitting accuracy for high pollution months in February, April, and November is higher than the annual mean, while July shows the opposite trend. The coefficient of variation for the importance rankings of the seven key explanatory variables exceeds 30% for both monthly and annual means. Among these variables, building density exhibited the highest coefficient of variation, at 123%. Building density and parking lots density demonstrate strong explanatory power for most months and exhibit significant interactions with other variables. Land use factors such as wetlands fraction, croplands fraction, park and greenspace fraction, and forests fraction have significant driving effects during the summer and autumn seasons months. The research on time scales aims to more effectively reduce PM_2.5 levels, which is essential for developing refined urban planning strategies that foster healthier urban environments. Full article

Intensive farming in urban suburbs often causes habitat loss, soil erosion, wastewater discharge, and agricultural productivity decline, threatening long-term benefits for the local community. We developed a nature-based solution for sustainable land restoration by establishing “Green Treasure Island” (GTI). The aim of this study is to evaluate the ecological restoration effectiveness of GTI and explore its feasibility and replicability for future applications. The core eco-functional zone of GTI—a 7 hm² forested wetland—embedded a closed-loop framework that integrates land consolidation, ecological restoration, and sustainable land utilization. The forested wetland efficiently removed 65% and 74% of dissolved inorganic nitrogen and phosphorus from agricultural runoff, raised flood control capacity by 22%, and attracted 48 bird species. Additionally, this biophilic recreational space attracted over 3400 visitors in 2022, created green jobs, and promoted local green agricultural product sales. Through adaptive management and nature education activities, GTI evolved into a landmark that represents local natural–social characteristics and serves as a publicly accessible natural park for both rural and urban residents. This study demonstrates the feasibility of creating GTI for improving ecosystem services, providing a practical, low-cost template that governments and local managers can replicate in metropolitan rural areas worldwide to meet both ecological and development goals. Full article

Currently, studies in green infrastructure have developed different wetland park value evaluation systems, and various criteria to measure urban economic development have been proposed. However, these criteria are not widely adopted, and there is a lack of investigation on the relationship between wetland parks and urban economic development. The existing literature indicates that the specific impact factors of wetland parks on urban economic development have not been further explored. Therefore, this study builds on previous theoretical research to develop a conceptual model with 12 hypotheses, followed by a questionnaire survey method to obtain data. The questions have been developed for each of five variables in the conceptual model to validate the research hypotheses that have been contextually modified according to the uniqueness of different wetland parks based on previous classic scales, namely, ecological value, recreational value, resource attraction, a diversified industrial structure, and economic expectation. This study aims to investigate how wetland parks promote urban economic health through ecological value and recreational value, particularly their indirect role in fostering diversified industrial structure, resource attraction, and economic expectations. Structural equation modeling with the Statistical Package for the Social Sciences (SPSS) 26.0 and the Analysis of Moment Structures (AMOS) 24.0 has been used for validating the hypotheses. The findings in this paper highlight that recreational value has the most significant impact on a diversified industrial structure that, in turn, has a highly significant positive impact on both resource attraction and economic expectations. In addition, the influence of ecological value on urban economic outcomes largely depends on recreational value as a mediator. Two significant impact pathways have been further identified: (1) from ecological value, recreational value, and a diversified industrial structure to resource attraction; and (2) from ecological value, recreational value, and a diversified industrial structure to economic expectations. Further, the managers and developers of wetland parks need to fully preserve the ecological value of the parks and optimize their recreational value before embarking on new development projects. The theoretical contribution of this paper lies in uncovering the direct and indirect effects of ecological value and recreational value on diversified industrial structure and resource attraction, emphasizing the crucial role of recreational value in driving economic diversification. The practical implications are reflected in providing concrete pathways and strategies for urban planners and policymakers to optimize the ecological and recreational value of wetland parks, thereby promoting urban economic development. Full article

Draining wetland landscapes accelerates climate change, and multilateral support is therefore needed to speed up the transition to new land uses. This paper examines perceptions of ecosystem services (ES) in wetland areas in scientific and civic assessments. The case study area is Denmark’s largest drained wetland system, which is notable for its carbon sequestration potential. The area’s transformation efforts involving public participation offer a unique chance to examine differences between scientific and civic perceptions of ES. This exceptional case is ideal for revealing contextual differences, trade-offs, and controversies between scientific and civic perceptions of ES. Millennium ES Assessment and CICES are used as a conceptual framework for understanding and mapping human–nature interactions in a nature park. However, these systems are, in practice, not sufficiently developed to identify how citizens understand and value ES in real life. Therefore, we analyse perceptions using interviews, collaborative mapping, and media analysis. We compare these to scientific ES mappings based on local data, literature reviews, and fieldwork. The paper concludes that (1) scientific ES asymmetries are important; (2) environmental blind spots in scientific ES are due to its approach to knowledge collection; (3) citizens’ blind spots are due to their everyday life focus and tabooing the issue of local climate mitigation; and (4) science-based ES assessments and accounts are disconnected from local ES controversies. We argue that identifying ES controversies through various scientific methods may improve climate mitigation and restoration efforts if community planning becomes involved. Full article

Establishing a resilient bird habitat network (BHN) and identifying ecological strategic areas for protection are critical for conserving biodiversity and maintaining ecosystem stability in wetland cities. However, existing ecological network studies often overlook dynamic resilience that incorporates explicit species information, and their scenario-based assessments lack systematic evaluation metrics. This study, using Wuhan—an international wetland city—as a case study, integrates Maximum Entropy (MaxEnt), remote sensing ecological index (RSEI) and circuit theory to identify a high-quality BHN. A comprehensive resilience assessment and optimization framework is developed, grounded in structure–function–quality indicators and informed by resilience and complex network theory. Key findings include: (1) The network comprises 147 habitat patches and 284 ecological corridors, demonstrating marked spatial heterogeneity. Habitats are predominantly located in the southern and southwestern regions of Wuhan, concentrated in contiguous green spaces. In contrast, habitats in the urban core are fragmented and small. Corridors are mainly distributed in the southwestern and central metropolitan areas. (2) Under deliberate attack, considering resilience centrality, the network’s resilience declined more slowly than in scenarios based on traditional centrality measures. Across combined node and corridor attack simulations, two critical resilience thresholds were identified at 30% and 50%. (3) The ecological strategic space is primarily composed of key habitat patches (58, 108, 117, and 27) and corridors (119–128, 9–12, 122–147, 128–138, 76–85, and 20–29), mainly located in the southern region of Wuhan, particularly around Liangzi Lake and Anshan National Wetland Park. This study advances a dynamic framework for BHN resilience assessment, planning, and restoration, providing scientific guidance for enhancing ecological security and biodiversity conservation in urban wetland environments. Full article

The microbial community is one of the key indicators for evaluating the health of alpine marsh wetlands, and understanding the composition and health of alpine wetland communities provides a scientific rationale for conservation and restoration efforts. Taking the alpine marsh wetlands in Qilian Mountain National Park, Qinghai Province, as the research object, 27 soil samples (0–30 cm depth) were collected in July 2024 from three types of wetlands: non-degraded (ND), low-level degraded (LD), and heavily degraded (HD). Using high-throughput sequencing, PICRUSt2 functional prediction, nonmetric multidimensional scaling (NMDS), and redundancy analysis (RDA), we analyzed the bacterial community structure and functional characteristics as well as the soil physicochemical properties across different degradation levels and soil depths. Pearson correlation analysis and RDA were used to identify key soil indicators influencing microbial community characteristics. The results showed that (1) compared to ND, the relative abundance of Acidobacteriota increased from 12.3% to 23.7%, and that of Pseudomonadota increased from 28.5% to 35.1% in HD wetlands. Meanwhile, the Shannon index rose from 5.31 in ND to 6.52 in HD, indicating significantly increased microbial community diversity and complexity with wetland degradation (p < 0.05). (2) Vertically, the six major primary metabolic functions gradually weakened with increasing soil depth in all three types of wetlands, the relative abundance of Proteobacteria decreased from 0 to 30 cm, and the α-diversity indices of soil bacteria also declined with depth. (3) Compared to ND, LD and HD showed significantly lower soil moisture content, organic matter, and total organic carbon (p < 0.05), while total potassium and pH increased significantly (p < 0.05). With increasing depth, total nitrogen significantly decreased across all degradation types (p < 0.05). Bacterial diversity, as measured by the Shannon and Simpson indices, showed a significant correlation with several soil properties (moisture, organic matter, total nitrogen, total potassium, cation exchange capacity, and total organic carbon; p < 0.05). Furthermore, pH emerged as a primary environmental driver shaping microbial community structure across different soil depths. These findings offer technical guidance and a theoretical framework for comprehending the degradation and restoration dynamics of alpine marsh wetland ecosystems in the Qilian Mountains. Full article