[Objective] Climate change has intensified global social risks and ecological crises. The increasing frequency of climate hazards such as heatwaves and extreme precipitation, combined with the persistent degradation of forests, soils, and other ecosystems, has become a critical constraint on the sustainable development of human societies. In response to climate change, the Intergovernmental Panel on Climate Change (IPCC) has proposed two overarching strategies: climate mitigation and climate adaptation. Climate adaptation refers to reducing climate-related risks by decreasing human vulnerability or safeguarding ecosystem service functions, and ecological restoration is widely regarded as one of the key approaches to climate adaptation. Ecological restoration can effectively enhance ecosystem services, such as increasing carbon sequestration, reducing surface temperature, and improving water conservation capacity—thereby demonstrating substantial potential for strengthening climate adaptability. However, although existing standards and practices of territorial ecological restoration repeatedly emphasize the integration of climate adaptation considerations, the specific types of climate adaptation within territorial ecological restoration, as well as the pathways and methods for identifying restoration areas and determining their priority with climate adaptation as a core objective, remain insufficiently defined. Therefore, clarifying climate adaptation types relevant to territorial ecological restoration and developing robust identification and priority-setting pathways and methods constitute an urgent research agenda.
[Methods] Taking the Chengdu-Chongqing urban agglomeration as the study area, from an exposure−sensitivity−resilience perspective, three types of territorial ecological restoration zones for climate adaption are defined: climate-exposed restoration zone (CERZ), climate-sensitive restoration zone (CSRZ), and climate-resilient restoration zone (CRRZ). The research route of this study consists of three major steps. 1) Based on the concepts of CERZ, CSRZ, and CRRZ and previous research findings, sample datasets and a double-layer indicator system comprising a “core-characteristic factors” were established to construct the machine learning dataset. 2) An ensemble machine learning model integrating three algorithms—maximum entropy (Maxent), random forest (RF), and categorical boosting (CatBoost)—through logistic regression (LR) was developed. The model performance was evaluated, and the spatial extents and restoration priorities of CERZ, CSRZ, and CRRZ were identified. 3) Differentiated response strategies were proposed according to the identification results and characteristics of CERZ, CSRZ, and CRRZ.
[Results] 1) Compared with the single-layer system, the double-layer framework improves the identification performance by approximately 5%, and the ensemble model improves it by around 3% compared with individual algorithms. 2) Both CERZ and CSRZ show more than 20% of areas at medium or higher restoration priority, indicating an urgent need for ecological restoration in the study area. Meanwhile, CRRZ with medium or higher restoration priority accounts for over 50% of the Chengdu-Chongqing urban agglomeration, suggesting that regional resilience enhancement remains a long-term and challenging task. The spatial patterns of restoration priority for the three zones exhibit the following characteristics. For CERZ, the proportions of restoration priority from high to low are 4.98%, 10.56%, 13.38%, 19.77% and 51.31%. Restoration areas above medium priority total 53,020.54 km2, mainly distributed in the karst regions of southern Sichuan and the Three Gorges Reservoir Area in northeastern Chongqing. For CSRZ, the proportions from high to low are 4.63%, 9.49%, 12.74%, 36.31% and 36.83%. Restoration areas above medium priority total 49,252.83 km2, exhibiting more fragmented patches and lower clustering than CERZ. Unlike CERZ, restoration priority increases within medium and large cities, especially in areas characterized by fragmented vegetation and dense river nets. For CRRZ, the proportions from high to low are 11.50%, 26.60%, 26.27%, 18.61%, 17.02%. Restoration areas above medium priority total 118,035.92 km2, showing both concentrated and dispersed patterns across low-altitude plains and hilly regions in the central parts of the Chengdu-Chongqing urban agglomeration. 3) CERZ aims to integrate engineering, ecological, and economic measures to effectively reduce the direct damage caused by extreme climate events. CSRZ aims to take river basins or key ecological function areas as spatial units to promote the recovery of ecological functions and the construction of ecological networks. CRRZ aims to advance the coordinated development of a green economic system and green infrastructure networks.
[Conclusion] By building double-layer indicator system and ensemble machine learning model, this study clearly reveals the differentiated patterns of territorial ecological restoration in the Chengdu-Chongqing urban agglomeration from an exposure−sensitivity−resilience perspective. The findings provide a replicable framework and technical reference for the scientific and rapid identification of the key areas and nodes of territorial ecological restoration, optimizing restoration layouts and resource allocation, and enhancing regional climate adaptability. In the future, our research may incorporate higher-resolution datasets of samples and indicators to further refine the identification and planning of territorial ecological restoration zones.
[Objective] The Earth’s ecosystems are facing the twin challenges of climate change and rapidly accelerating biodiversity loss. Global warming has increased both the frequency and intensity of extreme weather events. At the same time, as the global population has surpassed eight billion, rapid urbanization has continued to replace large areas of natural habitat with artificial ecosystems, leading to a persistent decline in native urban biodiversity. Conventional approaches to urban greening have mainly focused on visual landscaping and aesthetic improvement. This aesthetic-driven paradigm, which reconstructs vegetation primarily for appearance, has led to highly homogenized urban plantings. Native species are commonly excluded from such practices. As a result, the constructed plant communities often fail to match local biogeographical conditions and are unable to initiate natural successional processes on their own. Consequently, they provide inadequate, low-quality habitat for indigenous fauna such as insects, birds, and small mammals.The frequent use of herbicides and pesticides, combined with intensive understory mowing, has further degraded many artificial green spaces into “green deserts,” where vegetation remains but essential animal life is largely absent. Long-term reliance on such high-input, high-intensity, and carbon-intensive maintenance practices conflicts with the goals of sustainable, low-carbon development. This highlights the need to establish an integrated theoretical and technical framework for urban near-natural forests, which should achieve low construction and maintenance costs while supporting high ecological resilience and strong carbon-sequestration capacity. This study aims to contribute scientific grounding and practical guidance for mitigating climate change and reversing biodiversity decline, and to offer a replicable and scalable approach rooted in contemporary Chinese ecological practices.
[Methods] The study began with a systematic review of the origins, development, and conceptual foundations of the “near-natural” philosophy in ecological science and restoration practice. Building on more than two decades of empirical research, long-term monitoring, and demonstration projects conducted by our interdisciplinary team, the cosuccession hypothesis was translated from extensive field observations into practical ecological application. Based on these foundations, we propose a coherent framework for developing urban near-natural forests. The framework is structured across five interrelated components: guiding philosophy, foundational principles, theoretical basis, methodological pathways, and technical system.The framework draws on the philosophies of mountains, waters, forests, farmland, lakes, grasslands and deserts as a community of life, a community of life for man and nature, and the three ecological perspectives. It highlights a transition from “pseudo-nature and false ecology” toward “near-nature and true ecology.” It focuses on the coordinated restoration and functional enhancement of the five main categories of urban ecological space, including green spaces, forests, wetlands, croplands and garden lands. The near-natural ecological restoration serves as the primary implementation pathway. The establishment of resilient, functionally rich, regionally characteristic landmark biological communities is identified as the long-term restoration objective. Together, these elements form a fully operational, climate-adaptive, and functionally diverse technical system for urban near-natural forests guided by the cosuccession hypothesis.
[Results] Long-term field observations show that urban near-natural forests, which are established by simulating the species composition and structural characteristics of zonal climax communities with native species as the primary components, can effectively support natural successional processes. Once succession begins, indigenous fauna such as insects, birds, and small mammals gradually colonize these restored habitats. Dynamic ecological interactions were commonly observed during this process, including population turnover among different biological groups. These findings indicate that native plant communities provide habitat conditions that support the return of indigenous animals. In turn, the ecological roles of these animals promote plant communities toward more complex and stable successional stages. Recognizing these symbiosis-coevolution dynamics broadens the traditional plant-centered understanding of succession. Importantly, this study systematically traces the evolutionary process of urban near-natural restoration, integrating over two decades of empirical research and localized application practices, and proposes the cosuccession hypothesis for native species. This hypothesis not only provides a theoretical foundation linking classical ecological succession with practical restoration goals but also emphasizes the coordinated co-development of flora and fauna in urban ecosystems, highlighting the functional interdependence of biological communities at multiple scales. Ecological restoration guided by this hypothesis integrates the natural processes of classical succession with the goal-oriented objectives of restoration practice. Two main technical pathways link theory to application: 1) climate-adaptive design, which operates at the ecosystem scale across different vegetation zones, addressing large-scale climatic and environmental gradients, and 2) habitat-adaptive design, which focuses on the local community scale to optimize species interactions and microhabitat conditions at specific urban sites.
[Conclusion] These pathways guide the establishment of diversified communities, including construction, stewardship and management, and monitoring and evaluation. A key innovation is the development of multifunctional “landmark” biological communities that simultaneously enhance climate-habitat adaptability, maintain high biodiversity, and provide ecosystem services including carbon sequestration, water retention, and aesthetic value. Furthermore, this research refines and expands the theoretical framework of urban near-natural forest restoration, offering a comprehensive paradigm in which climate-adaptive design operates at the ecosystem scale across vegetation zones, and habitat-adaptive design focuses on the local community scale, together supporting multifunctional, climate-resilient, and self-organizing urban ecosystems. The study provides both conceptual and technical innovations, bridging ecological theory and applied urban restoration, and establishes a China-specific approach that can inform global near-natural urban forest practices. By emphasizing functional diversity, resilience, and ecological authenticity, this work contributes a robust scientific and practical foundation for transforming conventional urban green spaces into sustainable, self-regulating and ecologically integrated urban ecosystems.
[Objective] Under the dual pressures of rapid global climate change and the high-density urbanization strategy involving cross-river expansion, the Xi’an section of the Wei River Basin constitutes a critical ecological barrier in Northwest China. However, this region currently faces unprecedented challenges characterized by the superimposition of ecological degradation and intensifying climate risks. The increasing concentration of high-intensity construction activities along the riverfront has triggered a cascade of ecological issues, most notably the fragmentation of riverine floodplains, the shrinkage of natural wetlands, and a significant reduction in hydrological connectivity. These disruptions have severely threatened the stability of the regional ecosystem and undermined its service capacity. More critically, the rapid conversion of land use has heightened the region’s exposure to compound climate risks, specifically the coupling effects of the urban heat island (UHI), Urban Waterlogging, and the urban dry island (UDI). There is a growing spatial mismatch between the rigid expansion of urban boundaries and the dynamic demands of ecological security, leading to a “supply-demand dislocation” in climate resilience. Traditional static planning methods often fail to address these dynamic uncertainties. Consequently, there is an urgent need to construct a scientifically grounded ecological protection and restoration framework that shifts from “passive defense” to “active adaptation”. The primary objective of this study is to clarify the ecological baseline and vulnerability of blue-green spaces in the study area and to propose a “hierarchical and categorical” resilience planning strategy. This strategy aims to delineate precise control units and formulate differentiated restoration measures, thereby guiding the implementation of ecological spaces within detailed planning units and coordinating high-quality urban development with long-term regional ecological security.
[Methods] Focusing on the Xi’an section of the Wei River Basin, this study introduces the systematic conservation planning (SCP) theory to establish a comprehensive analytical framework titled “ecological status assessment−future scenario simulation−hierarchical and categorical delineation−planning strategy response”. The methodology proceeds in three rigorous steps. Firstly, the study integrates multi-source datasets—including digital elevation models, land-use data, remote sensing imagery, and administrative vector data—to conduct a systematic baseline quantification. The InVEST model is applied to assess habitat quality and ecological sensitivity, identifying the current service functions and fragility of blue-green spaces. Secondly, grounded in the Master Plan for Xi’an Territorial Spatial Development (2021−2035), the research employs the XGBoost model and scenario simulation techniques to predict the spatiotemporal patterns of compound climate risks. The study simulates the distribute on and intensity of UHI, waterlogging risk, and UDI effects under future land-use scenarios (2035), quantifying the spatial coupling relationship between ecological value and multiple risk stressors. Thirdly, by embedding SCP principles such as conservation target setting and cost-benefit analysis, the study utilizes the Zonation 5 model to overlay the baseline ecological importance with future risk gradients. This process allows for the quantitative identification of protection priorities and the formulation of spatial optimization strategies that respond to both current ecological deficits and future climate stressors.
[Results] The integrated analysis yields three critical findings regarding the ecological pattern and risk distribution of the study area. 1) Spatial congruence between high value and high sensitivity: The ecological status assessment reveals a pronounced spatial overlap between high-value ecological patches and highly sensitive areas. Quantitative analysis indicates that areas with high habitat quality (Class I and II) account for 59.21% of the total blue-green space, closely aligns with the 47.11% coverage of highly sensitive areas (Class I and II). These categories exhibit strong spatial consistency, being primarily concentrated in riparian wetlands and riverine forests. This finding underscores that the region’s most valuable ecological assets are simultaneously its most fragile, possessing limited resilience against human interference. 2) Agglomeration of compound climate risks: The future scenario simulation demonstrates that, by 2035, the high-value areas for superimposed risks (UHI, waterlogging, and UDI) will further cluster in the built-up urban zones. These high-risk areas, representing the structural conflict zones at the urban expansion interface, account for 24.3% of the total study area. This suggests a deepening conflict between urban densification and environmental comfort. 3) Hierarchical and categorical spatial optimization: Based on these findings, the study adopts a conservation priority threshold of 0.7. By integrating the ecological baseline conditions with future risk boundaries, the research delineates a “4-Level, 8-Type” blue-green space system. The four hierarchical levels correspond to distinct ecological roles: ecological function enhancement, composite utilization, network optimization, and quality improvement within built-up areas. The eight functional units are explicitly defined as follows: Core conservation units, urban wilderness units, restoration and compensation units, cultural heritage units, urban agriculture units, public service units, ecological infrastructure units, and urban recreation units. For each unit type, specific spatial boundaries and differentiated restoration strategies are formulated to ensure precise governance.
[Conclusion] By integrating SCP theory with multi-scenario simulations, this study develops a dynamic and quantitative methodological framework suitable for the hierarchical and categorical determination of blue-green spaces under multi-climate risks. The research moves beyond static assessment by incorporating future climate uncertainties into the conservation decision-making process. The findings confirm that establishing a prioritized, unit-based control system is essential for managing the trade-offs between conservation and development in high-density areas. The proposed “4-Level, 8-Type” system provides a transferable framework for enhancing regional ecological resilience. Furthermore, the outcomes offer strong theoretical support and actionable indicators for the integration of ecological requirements into territorial spatial detailed planning, ensuring that macro-level ecological security patterns are effectively translated into micro-level implementation measures in rapidly urbanizing river basin regions.
[Objective] Urbanization has fragmented ecological habitats, threatening urban ecosystem sustainability. Ecological networks are crucial for maintaining resilience, with dynamic interactions between network systems and urban development. Amid the green transformation of cities, refining the framework for optimizing urban ecological networks is essential. However, current research mainly focuses on static optimization, neglecting the dynamic evolution between nature and urbanization, and overlooks land use/cover changes in mid-to-small-scale areas, weakening the social functions of ecological networks. This study aims to address the limitations of current static approaches to urban ecological network optimization by investigating the dynamic interplay between urbanization and ecological network resilience. Specifically, focusing on Haizhu District, Guangzhou, this research will discuss the following issues. 1) Simulate future urban development scenarios and potential disturbances, considering spatio-temporal dynamics and land use/cover changes at a mesoscale; 2) Develop and apply a framework for proactively measuring the resilience of urban ecological networks under these dynamic scenarios; 3) Propose targeted design responses and optimization strategies to enhance ecological network resilience, incorporating principles of regional coordination; 4) Ultimately, inform sustainable urban development orientations and operational strategies for Haizhu District, contributing to a more resilient and ecologically sound urban environment.
[Methods] This study develops a theoretical framework to analyze the dynamic coupling between urban development and ecological networks, and proposes a new concept of "Urban-Wetland Complex" and summarizes it along with its characteristics. The framework is applied to Haizhu District, Guangzhou (90.42 km2), a representative wetland urban area in the Pearl River Delta, serving as a case study. Multi-source data, including land use and land cover change (LUCC) data, remote sensing imagery, and socio-economic statistics, are integrated to parameterize the patch-generating land use simulation (PLUS) model. This model is then used to simulate three future development scenarios: 1) natural evolution (baseline scenario without policy intervention), 2) ecological priority (scenario that maximizes ecological benefits), and 3) economic priority (scenario that maximizes economic efficiency). Based on multi-temporal land-use classification maps derived from these simulations, ecological networks are constructed under each scenario. A dual-dimensional resilience assessment model, encompassing both structural and functional aspects, is proposed to quantify the resilience of the network. Structural resilience is evaluated using Graph Theory metrics, specifically connectivity probability and network closure. Functional resilience is assessed through betweenness centrality analysis and node-deletion experiments, focusing on key node identification rate and overall network robustness.
[Results] 1) Structural and functional resilience mechanisms: Structural resilience was primarily influenced by the degree of source fragmentation, the average length of ecological corridors, and network transmissibility. Functional resilience, in contrast, depended on the number of critical nodes and their sensitivity to node removal processes. The comparison of network resilience before and after node removal effectively identified key ecological nodes within the network. 2) Spatial patterns of ecological sources: Ecological sources in Haizhu District were largely consistent with the Pearl River network, wetland parks (e.g., Haizhu Wetland) and existing urban green space systems, reflecting the dominance of wetland−river interactions in shaping the ecological structure. 3) Scenario-based resilience performance: Under the natural development scenario, network connectivity, disturbance resistance, and connection efficiency were the highest, indicating superior structural resilience. The shortened average corridor length enhanced species migration efficiency, leading to improved overall network performance. Under the urban expansion scenario, the ecological network displayed a strong dependence on a limited number of critical nodes, resulting in weakened functional resilience and reduced spatial redundancy. Nodes were highly concentrated south of the wetlands, aligning with the phenomenon of ecological islanding induced by intensive development. Under the ecological priority scenario, the network exhibited the highest resilience threshold and overall stability. Secondary nodes such as Dawei Park and the riverside green belts formed a "core wetland−multi-tiered pivot" structure, enhancing spatial equilibrium and redundancy. However, the longer corridor paths in this scenario were more frequently interrupted by urban infrastructure and human disturbance.
[Conclusion] This study advances on previous research on the identification of key ecological patches and corridors by incorporating a spatiotemporal perspective into the analysis of urban ecological networks. By assessing the evolution of landscape connectivity under multiple development scenarios, this study reveals the dynamic interactions between urban expansion and ecological resilience. The study further refines the methodological framework for evaluating urban ecological networks, establishing a three-dimensional analytical system integrating "network−resilience−potential". This framework not only provides scientific guidance for determining regional ecological development directions and optimizing land-use planning but also serves as a theoretical reference for understanding the dynamic coupling between nature and city in high-density urban environments. Ultimately, the findings contribute to bridging the gap between ecological modeling and spatial design, supporting the construction of adaptive, resilient, and sustainable urban ecological systems.
[Objective] Against the dual pressures of global climate change and rapid urbanization, the urban heat island effect is becoming increasingly severe. Urban green spaces offer a near-natural approach to mitigating the heat island effect. Their cooling effects are influenced by biotope characteristics and the differences among biotope types. Therefore, typologically revealing the impact patterns of urban green space biotope characteristics on cooling effects is crucial for improving the urban thermal environment and contributing to the construction of an ecologically livable environment.
[Methods] The study area is Around Taihu Lake region in the Yangtze River Delta, involving four cities (Suzhou, Wuxi, Changzhou, Huzhou) encompassing 16 county-level administrative units, covering approximately 13,000 km2. This region, centered around Taihu Lake, features a dense river network, numerous lakes, and diverse types of urban green spaces containing various biotopes. However, the urban heat island problem has become increasingly severe in recent years. Consequently, optimizing biotope type configuration during urban ecological restoration to enhance the cooling effect of green spaces has become a significant focus for building an ecologically livable city in this region. This study first introduces a U-Net-ResNet50 backbone training network combined with high-resolution remote sensing images to build an intelligent identification model, overcoming the technical bottleneck of traditional methods struggling with large-scale, high-precision biotope surveys and classification. Building the intelligent identification model mainly involves four steps: 1) Using 25,983 satellite images from 508 green space samples as the model database. Subsequently, analyzing the composition characteristics of biotope elements in these 508 urban green space samples, the study identified 10 natural biotope elements as targets for manual annotation and semantic segmentation recognition. 2) Manually annotating local satellite images containing all biotope element types to create a foundational dataset for supervised learning model training. After model training and optimization, the supervised model was applied to annotate biotope elements in satellite images from other areas, ultimately producing the training and testing datasets required for the U-Net−ResNet50 network model. 3) A semantic segmentation platform was constructed using the PyTorch framework, with ResNet50 and U-Net as the backbone training networks. The prepared training set data was input for training, and a loss function was set to evaluate the model's robustness. Upon completion of training, the model achieved good stability and consistency. 4) Applying the trained and verified reliable model to Around Taihu Lake region. Subsequently, based on the intelligent identification results of urban green space biotope elements, this study used K-means clustering to derive subdivided biotope types. Next, using 30 m resolution land surface temperature retrieval data from a typical high-temperature day in 2022, this study employed mean and maximum land surface temperatures to characterize the cooling effect. Cross-analysis was used to reveal the differences in cooling effects among different biotope types and key influencing factors. Taking biotope types as the entry point, this research further refines the exploration of the cooling effects of urban green spaces. The study proposes differentiated preferential design guidance for biotopes, providing technical support for the precise ecological restoration of climate-resilient urban green spaces.
[Results] 1) A total of 6 primary-level and 39 secondary-level green space biotope types were identified through detailed classification. 2) The cooling effects of the primary biotope types were ranked in descending order: woodland biotope > waterfront composite biotope > vegetation composite biotope > farmland composite biotope > grassland biotope > hard-paved biotope. Urban-rural comparative results showed that the thermal environment stability of biotope types in suburban areas was significantly better than that in urban areas. 3) The cooling effects of various biotopes were influenced by the urban-rural gradient, with different key biotope characteristic factors identified as drivers. The cooling effect of woodland biotopes was mainly driven by topography and slope. For vegetation composite biotopes, vegetation structure was the core factor in urban areas, while a synergistic effect of topography and forest stand structure was observed in suburban areas. The cooling effect of waterfront composite biotopes was primarily governed by multiple factors, including water surface ratio, vegetation structure, and tree canopy coverage. Within farmland composite biotopes, agroforestry models with higher tree canopy coverage demonstrated significant cooling effects. 4) Based on the heterogeneity in the spatial distribution of cooling effects across different green space biotope types along the urban-rural spectrum, biotope types with high cooling efficacy were preferentially selected. For urban areas characterized by limited land resources, high development intensity, and reliance on single biotope element drivers, design strategies for specific biotope types were precisely targeted and regulated. For suburban areas, which benefit from a better ecological baseline and rely on the synergistic driving effects of multiple biotope elements, design strategies for specific biotope types were systematically enhanced.
[Conclusion] The U-Net-ResNet50 intelligent identification model facilitates the precise and batch-processing-enabled identification and classification of urban green space biotope elements. This approach overcomes the technical limitations of traditional biotope element identification methods, namely, low efficiency and restricted sample sizes, and provides a transferable intelligent methodology for precise biotope mapping and classification in related fields. The study elucidates the differential patterns in cooling effects and their driving factors across various urban green space biotope types, thereby robustly supporting the preferential design of green space biotopes. It offers a valuable reference for achieving climate-resilient, near-natural ecological restoration in urban green spaces.
[Objective] Against the backdrop of accelerating global urbanization, the conservation and restoration of urban biodiversity have become critical interdisciplinary issues in landscape architecture, ecology, and urban and rural planning. Spontaneous vegetation, as a key component of urban flora, has garnered increasing attention due to its adaptability to urban environments, low maintenance requirements, and potential in preserving regional biodiversity. However, the distribution and functional realization of urban vegetation, especially spontaneous vegetation, are shaped by the combined effects of macro-climatic conditions, meso-scale urban environments, and micro-scale habitat characteristics. Existing research often suffers from scale fragmentation, wherein macro-scale studies focus on regional climatic gradients but seldom integrate urban design needs, meso-scale analyses address urban structural impacts but fail to link regional ecological contexts with site-specific designs, and micro-scale investigations reveal how microhabitat conditions influence species establishment but rarely attribute these effects to broader climatic or urban-scale drivers. This lack of multi-scale linkage hampers a systematic understanding of the mechanisms underlying urban spontaneous vegetation diversity and the development of scale-adapted application strategies. To address this gap, this study aims to investigate the driving mechanisms by which climatic differences affect the distribution patterns of urban spontaneous vegetation diversity across multiple scales, and establish a corresponding near-natural ecological restoration technical system, thereby addressing the prevalent scale mismatch issue in current urban biodiversity restoration practices.
[Methods] This study was conducted in Jilin Province, which exhibits a distinct humid−semi-humid−semi-arid macro-climatic gradient from southeast to northwest. The research framework encompasses three macro-scale climatic subregions, nine meso-scale prefecture-level cities, and five micro-scale habitat types within urban built-up areas. A total of 3,267 sample plots were surveyed using the Braun-Blanquet phytosociological approach during the complete growing season (May to September 2024). All spontaneously occurring vascular plant species (including naturally colonized herbs, escaped cultivated individuals, and regenerated seedlings of woody plants) within each 1 m×1 m quadrat were recorded, with their height and coverage measured. Data analyses focused on both alpha diversity (Patrick richness index, Shannon-Wiener diversity index, and Pielou evenness index) and beta diversity (based on Jaccard and Bray−Curtis distance matrices). Statistical comparisons were performed using Kruskal−Wallis tests with post-hoc Dunn tests for alpha diversity, and PERMANOVA with principal coordinate analysis (PCoA) visualization for beta diversity. All analyses were conducted in R 4.5.1, with a significance threshold of p＜0.05.
[Results] 1) A total of 605 spontaneous plant species belonging to 85 families and 342 genera were recorded across the nine cities. Asteraceae, Fabaceae, Rosaceae, and Poaceae were identified as the dominant families. Perennial herbs constituted the most abundant life form (41.8%), and native species accounted for 78.2% of all recorded species. 2) At the macro scale, alpha diversity showed a pattern of MIDDLE > WEST > EAST. Beta diversity analysis revealed highly significant differences among the three climatic subregions (p<0.001), although the explanatory power of inter-group variation was low (R 2<1.5%). PCoA ordination based on Jaccard and Bray−Curtis distances indicated that community differentiation followed different ecological gradients: species presence−absence patterns varied mainly along PC1 for the MIDDLE and EAST, while the WEST varied along PC2. 3) At the meso-scale, Changchun exhibited significantly higher alpha diversity than all other cities. Beta diversity patterns differed between species presence−absence and abundance-based dimensions: based on Jaccard distance, Baishan and Tonghua showed high heterogeneity in species composition, whereas Bray−Curtis-based PCoA revealed two nearly orthogonal nested gradients, indicating that community abundance structures varied along two relatively independent ecological dimensions. 4) At the micro-scale, UG had the highest Shannon-Wiener diversity and Pielou evenness indices, while SG had the lowest values. RG and RAG exhibited highly similar species diversity composition and community structure. Beta diversity analysis further confirmed significant differences among most habitat types (p<0.001), though habitat type explained only a small fraction of total variation (R 2<1.13%). Notably, RG and RAG showed extensive overlap in PCoA ordination, suggesting that intensive and homogeneous management may override microclimatic filtering, leading to community convergence.
[Conclusion] The diversity patterns of urban spontaneous vegetation in Jilin Province are driven by a cascade of multi-scale climatic and anthropogenic factors. At the macro scale, climatic gradients shape regional species pools and broad life-form distributions, though their direct explanatory power for inter-regional variation is limited. At the meso-scale, urban functional characteristics and localized climate modifications (e.g., heat island effects) interact to reshape diversity patterns, sometimes decoupling them from macro-climatic expectations. At the micro-scale, habitat-specific microclimates and management intensities act as strong filters, with high-intensity management leading to functional homogenization across otherwise distinct habitats. Based on these findings, a scale-adapted near-natural restoration strategy system is proposed. At the macro-scale, implementing differentiated plant selection and community design according to climatic subregion characteristics. At the meso-scale, tailoring restoration approaches to urban functional types and local climate adaptations, and at the micro-scale, applying precise regulatory measures based on habitat-specific conditions and functional needs. This integrated multi-scale framework provides a scientific basis and practical guidance for biodiversity conservation and climate resilient ecological restoration in cold-temperate cities. Future research should incorporate multi-season dynamic monitoring to further elucidate the temporal dynamics and long-term sustainability of spontaneous vegetation communities in urban ecosystems.
[Objective] As one of the basic well-beings and primary needs for the survival and development of mankind, health is closely influenced by a variety of multidimensional and complex influencing factors. Leisure-time physical activity (LTPA) is a physical activity of large flexibility in such factors as activity strength, duration, location selection and others, and together with the outstanding regulation effect on the physiological and psychological aspects, has seen a continuous and gradually expanded role in daily life. It is therefore regarded as the most promising type of changeable physical activities. Urban parks as a spatial store of comprehensive health resources have been rooted in green space system. They are combined with various service resources, providing a physical environment for LTPA. However, the majority of current research on LTPA predominantly concentrates on the direct relationship between the environment and behavior. Visual and auditory cues are typically presented in a parallel manner, lacking joint modeling at the same spatiotemporal location. Emotional perception, as a crucial psychological pivot through which environmental cues influence behavior, has not undergone systematic scrutiny. This has led to difficulties in the precise implementation of relevant design strategies. In the context of park settings, visual and auditory cues frequently co-occur at the same spatiotemporal point. They may influence an individual's subjective evaluations of safety, pleasure, and vitality through emotional regulation, thereby affecting their activity intensity and inclination to remain in the area. Consequently, there is an urgent need to conduct empirical research using the framework of "audio-visual environmental elements−emotional perception−leisure physical activities".
[Methods] In this paper, 144 landscape nodes in Taizi River Park, Liaoyang City, Liaoning Province were classified meticulously. In terms of visual object, the image acquisition method is conducted on a sunny day, and the circumferential three pictures are shot for each landscape node. ArcGIS 10.8 software was applied to match the image with GPS spatial data. The mask2Former semantic segmentation model was applied to the image data. According to Mapillary Vistas dataset, leisure-time physical activity related image vectors were embedded to build customized model according to the research purpose. The acquired image data were analyzed by this method. Color features (color saturation, color richness, and color harmony) of obtained image were analyzed using K-means algorithm. A “human-machine duel” score sheet was used for the emotional evaluation of the environment. For the acoustics, the environmental sound cues and the source category for the audio part were noted according to the ISO/TS
[Results] Through the analysis of the audio-visual environment, emotional evaluation, and behavioral observation data collected in the field, this study has yielded a series of crucial findings. Visual and auditory elements within urban parks, including the blue view ratio, sky openness, natural sounds, and light guidance, can significantly enhance visitors' positive emotional experiences (such as a sense of security, vitality, and fulfillment). This, in turn, further increases the likelihood of light-intensity and moderate-intensity LTPA. Emotional perception exerted a partial mediating effect along multiple pathways, providing quantitative evidence for the "environment−emotion−behavior" framework. Specifically, sky openness and natural sound sources influenced light LTPA through emotional perception, while spatial enclosure affected moderate LTPA. These results suggest that an open skyline and a favorable water-related environment are conducive to eliciting positive emotions and promoting gentle physical activities. Moreover, moderately enclosed green spaces significantly facilitate moderate activities by enhancing the sense of security. In contrast, no significant emotional mediation pathway was identified for high-intensity physical activities. This might be attributed to the fact that high-intensity activities are more goal-driven and performance-oriented. Environmental factors primarily act on such activities by directly influencing aspects such as safety and convenience, rather than indirectly through emotions.
[Conclusion] This research delved into the interrelationship of "environment−emotion−behavior" within the context of urban parks, quantitatively validating the pivotal mediating role of emotional perception in the process where the audiovisual environment influences LTPA. This has advanced the comprehension of the mechanisms through which environmental elements facilitate behaviors. On a practical level, the research findings offer significant implications for enhancing the health-promoting benefits of urban parks. Looking ahead, the analytical framework and optimization strategies established in this study can serve as a theoretical foundation and practical reference for related disciplines. They can also drive the research agenda of integrating emotional perception into environmental interventions to promote behavioral change, thereby providing a scientific underpinning for the creation of healthy cities and active spaces.
[Objective] The accelerated process of urbanization has intensified the urban heat island (UHI) effect, posing significant threats to public health and sustainable socio-ecological development. Urban fringe areas, characterized by their blue-green spaces (BGS), serve as critical ecological buffers. These spaces not only curb urban sprawl and mitigate the spread of the UHI effect but also provide essential peripheral cooling services to metropolitan cores. Consequently, enhancing the construction and functionality of BGS in these peripheral areas is of paramount importance for alleviating urban thermal environmental pressure and fostering coordinated ecological development between urban and rural landscapes. However, rapid urbanization has led to the increasing fragmentation of these vital BGS, which has severely impaired their ecosystem services, particularly their cooling capacity. While expanding green infrastructure is a direct approach, it is often infeasible under the constraints of limited land resources in densely populated regions. Therefore, a paradigm shift is required: instead of merely expanding the area of BGS, the focus should be on optimizing the connectivity among existing cooling sources to implement targeted and effective cooling strategies. Current research predominantly relies on qualitative descriptions or simplified linear models for thermal mitigation planning, resulting in a lack of robust and systematic analytical frameworks. This study aims to enhance cold source connectivity to improve the overall cooling efficiency of the urban fringe of megacities, thereby offering a novel, integrative analytical pathway for urban heat mitigation planning.
[Methods] Taking the Second Green Belt in Beijing as a case study, this study constructs an urban cooling network. Land surface temperature (LST) was retrieved from Landsat imagery to identify cold sources, and morphological spatial pattern analysis (MSPA) was applied to extract their core areas. Natural and socio-economic variables, together with landscape pattern indices, were incorporated as resistance factors. An XGBoost model combined with SHAP interpretation was employed to quantify the nonlinear relationships between these factors and LST, with absolute SHAP values used as weights to generate a resistance surface. Circuit theory was then applied to identify key cooling corridors and establish and optimize the cooling network. Complex network theory was subsequently employed to evaluate network performance before and after optimization.
[Results] LST retrieval revealed higher temperatures in the eastern, flatter, and more developed part of the study area, contrasting with the cooler, topographically complex western region with greater vegetation and water body coverage. The identified cool sources, predominantly located in the west, covered approximately 855.65 km2. MSPA of these cool islands led to the identification of 53 core areas as major cool sources, primarily clustered in the northwestern and southwestern sectors, with smaller, fragmented sources in the east. The XGBoost-SHAP analysis revealed the relative importance of the resistance factors: the proportion of impervious surface (PLAND_IMP, 33.7%) was the most significant, followed by NDVI (19.0%), Nighttime light (15.1%), Building Height (9.8%), and the proportion of green space (PLAND_GRE, 9.5%). PLAND_IMP, NL, and BH contributed positively to LST (increasing resistance), while PLAND_GRE and NDVI had cooling effects (decreasing resistance). The resulting resistance surface exhibited a spatial pattern consistent with the LST distribution, with high values in impervious-dominated areas and low values in heavily vegetated northwestern zones. The initial cooling network comprised 117 corridors spanning 52.9 km. The optimization process proposed adding 11 new nodes from pinchpoint analysis and modifying 8 structurally weak nodes. The final optimized network incorporated these changes, resulting in 33 additional corridors, significantly enhancing connectivity, particularly in the eastern part of the study area. Stability tests demonstrated the optimized network's superior robustness.
[Conclusion] This study enhances the cooling effectiveness of blue-green spaces in the peripheral zones of megacities by integrating computer science with landscape ecology and strengthening the connectivity among fragmented cold sources, thereby providing a structural basis for near-natural restoration. The resistance-surface construction is advanced by incorporating landscape pattern indices and vertical-dimension factors, enabling a more accurate representation of surface heterogeneity. Explainable machine learning is employed to capture nonlinear interactions among resistance factors, allowing the cooling network to better reflect underlying ecological processes. By accounting for complex environmental conditions and disturbances, the study proposes a function–structure coordinated optimization framework that integrates cold-source pattern enhancement, land-use regulation, ecological corridor construction, and multi-sector governance to improve cooling efficiency and network stability.
[Objective] Climate change, biodiversity loss, and environmental pollution are widely recognized as the triple planetary crisis. Among them, climate change has intensified the frequency and magnitude of extreme wind events, particularly typhoons, resulting in substantial impacts on ecosystems and human societies. China is located within the active typhoon belt of the northwest Pacific, where approximately 80% of annual typhoons make landfall. Coastal regions exhibit pronounced spatial heterogeneity in wind disaster risk due to complex interactions among topography, climate conditions, and socioeconomic development. Protected areas, as critical spatial units for biodiversity conservation and ecological security, are increasingly exposed to wind hazards. However, systematic assessments of wind disaster risk at the protected-area scale remain limited. Existing studies predominantly adopt the three-dimensional “hazard−exposure−vulnerability” framework proposed by the Intergovernmental Panel on Climate Change (IPCC). In this framework, hazard represents the intensity and frequency of disasters, exposure reflects the degree to which natural and social elements are affected, and vulnerability indicates the likelihood of system damage. While this framework has been widely applied to floods, earthquakes, heatwaves, and other natural hazards, its application to wind disaster risk in protected areas is still insufficient. In particular, previous studies often fail to integrate long-term hazard dynamics with ecological and socio-economic characteristics, limiting their ability to support targeted risk management and spatial planning.
[Methods] To address these gaps, drawing on the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, we developed a three-dimensional wind disaster risk assessment framework integrating hazard, exposure, and vulnerability. The framework combined multi-source environmental and socio-economic data to quantify wind disaster risk and reveal its spatial differentiation and temporal evolution. The Fuzhou Metropolitan Area was selected as the case study because it is located along China’s southeastern coast, characterized by frequent typhoon activity, diverse protected area types, and pronounced coastal-inland gradients, making it a representative region for examining wind disaster risks under climate change. Within this framework, wind disaster risk levels of protected areas in 1980 and 2020 were quantified and compared. Multi-criteria evaluation methods were applied to construct the hazard, exposure, and vulnerability indices, while the entropy weight method was used to reduce subjectivity in indicator selection. ArcGIS spatial analysis techniques, including spatial overlay,zonal statistics, and hotspot analysis, were employed to analyze the spatial patterns and temporal dynamics of wind hazards, exposure, vulnerability, and comprehensive risk. At the indicator level, meteorological, topographic, ecological, and socio-economic data were integrated to conduct comparative risk assessments across protected areas in the Fuzhou metropolitan area.
[Results] 1） Wind disaster risk exhibited a clear spatial pattern characterized by higher risk in the south (0.57) and lower risk in the north (0.09), with coastal protected areas generally facing higher risk levels than inland areas. Wind disaster risk showed clear spatial clustering, with high-risk protected areas (0.61−0.66) concentrated in the southern and southwestern regions, medium−high risk areas (0.500−0.550) in the central transition zone, and low-risk areas (≤0.01) mainly distributed in the northern and northeastern regions, showing a pronounced south−north decreasing gradient. 2）Exposure levels across protected areas were generally moderate to high, while vulnerability showed an overall increasing trend from 1980 to 2020, indicating growing sensitivity of protected areas to wind hazards over time. In 1980, high-exposure areas (0.59−0.62) were located in northwest mountains and central hills, and low-exposure areas (0.04) were along the eastern coast. By 2020, high-exposure zones persisted but declined (e.g., from 0.59 to 0.31), with low coastal exposure unchanged, showing stable spatial patterns and an overall decrease. 3）Comprehensive wind disaster risk differed markedly among protected area types, ranked from high to low as forest parks to scenic areas, nature reserves, wetland parks, and geological parks. High-risk protected areas, including Jiulihu Scenic Area, Dafeishan, and Biqing Forest Parks (0.54−0.57), clustered in the south and south-central region. Medium-risk areas (0.30−0.50) occupied central and coastal transitional zones. Low-risk areas, such as Dongchong Peninsula, Sandu’ao, and Baiyunshan Parks (≤0.20), were located in the north and inland mountains.
[Conclusion] Based on these findings, we proposed three planning optimization strategies for protected areas: optimizing functional zoning to reflect spatial risk differentiation, establishing dynamic wind hazard monitoring and early-warning mechanisms, and implementing pilot-based differentiated risk mitigation measures tailored to specific risk profiles. We analyzed wind disaster risks across temporal and spatial scales and visualized their dynamics through spatial mapping. Focusing on the protected area level, fine-scale spatial heterogeneity and temporal evolution patterns can be identified, which are often obscured in conventional assessments. By revealing the spatial patterns and evolution characteristics of wind disaster risk from a protected-area perspective, we provided an assessment framework that balances universality and practicality. The framework can offer practical support for climate-resilient planning and governance of protected area systems under ongoing climate change.
[Objective] Guided by the principle of advocating harmonious coexistence between humans and nature, linear recreational spaces have become significant places for people to explore and connect with nature. Currently, China is actively promoting the establishment of a natural reserve system centered on national parks. Building a system network of long-distance, multi-purpose and multi-target national trails faces various challenges. Therefore, it is necessary to draw experiences and lessons from regions with more mature outdoor recreation and trail system. As the second largest country in the world in terms of land area, Canada has successfully established a national trail system. Although its practice can bring us very valuable insights, it has been relatively understudied.
[Methods] This study takes the Trans Canada Trail (TCT), one of the world’s longest systems of multi-use recreational trails, as its primary case. Initiated in 1992, TCT has stretched over 29,000 km from the Atlantic to the Pacific to the Arctic oceans, through every province and territory, linking over 15,000 communities. It draws on relevant legislation, policies, and guidelines issued by responsible agencies, as well as official reports. Combining geographic information analysis with field investigations, it explores the planning, construction, and management practices of TCT. It focuses on the goals, standards and system for TCT’s classification, the universal accessible strategies, and the design of its signage system. The photos of field investigation demonstrate how different sections of TCT are designed to adapt to their various contexts. The study also explored how quantitative assessment of sustainable benefits could help enhance government and public support for the trail development. It also highlights four key characteristics of TCT’s operation model, namely the non-profit leadership, the collaborations among multiple stakeholders, financial sustainability, and ensuring public safety.
[Results] The TCT employs a composite classification approach that communicates trail information more clearly and helps users make better-informed decisions. It adopts a standardized framework based on Trail Management Objective (TMO), allowing for systematic evaluation of how well a trail’s physical design parameters align with its intended management goals, and enabling targeted management strategies. The surface and nodes of the trails are designed to adapt to their respective contexts, with distinct configurations tailored to natural, rural and urban settings. TCT’s universal accessibility is supported by physical design, users’ participatory design methods, and information services, as well as design guidelines and digital mapping tools used to establish a coherent signage system. Independent organizations have conducted quantitative evaluations of the economic, social, and environmental benefits of TCT to demonstrate its sustainability. The findings reveal that TCT can enhance the common vision of the nation, which helps TCT gain stronger support for its development and management from government agencies and the general public. The operation model of TCT is led by a non-profit organization, relying on the collaborative governance of the federal government, local authorities, communities, enterprises and indigenous people, which is the approach to address the challenges posed by fragmented land ownership and a complex social landscape. The sources of funds for the development and maintenance of TCT are relatively extensive. Although federal funds take up the major portion, more than one-third of the budget comes from other sources, such as private donors. These resources are mainly allocated to trail construction and maintenance, as well as outreach activities and volunteer participation. A sound financial audit and the financial system’s transparency are essential to sustain TCT’s operation. Furthermore, the public liability insurance is required to help reduce the operational risks and costs for the management entities.
[Conclusion] Facing numerous challenges, including vast territory, fragmented land ownership, complex environmental contexts, and the lack of a unified federal legal framework among others, one of the world’s longest national trail systems has been successfully established across Canada, with a nationally shared vision and high connectivity. Its practical experience enables us to gain meaningful insights. In the process of establishing a national trail system, China still faces several critical challenges that require immediate resolution: the absence of a cross-regional coordination mechanism has led to fragmentation in management; insufficient systematic policy guidance and technical standards hinder the improvement of trail system’s quality; over-reliance on government funding makes it difficult to establish a sustainable long-term investment mechanism; a scientific evaluation system has yet to be developed to achieve a dynamic balance between ecological conservation and social development; and effective public participation and multi-stakeholder collaboration mechanisms remain challenging to implement. The suggestions are listed as follows: 1) Establish a cross-regional collaborative governance mechanism, to enhance connectivity for large-scale trails, and to help connect China’s rich cultural and natural heritage; 2) Adopt a composite operational management system and a multi-stakeholder cooperation mechanism, and improve diversified funding mechanisms; 3) Formulate unified trail guidelines, to leverage the guiding and unifying role of trail guidelines to promote cross-regional design and maintenance cooperation; 4) Establish a sustainable evaluation system through quantitative assessment, to support multi-dimensional coordinated development of trails.
[Objective] The Tarim River Basin, a representative arid region, is characterized by unique climatic conditions, ecological fragility, and rich cultural heritage. The construction and evolution of oasis gardens in this area significantly influence the distribution of natural vegetation, desertification processes, and the rise and fall of oases. These gardens exemplify long-term human adaptation to extreme aridity, embodying profound indigenous knowledge and landscape construction wisdom. However, previous studies have largely remained at the level of phenomenological description and static analysis, lacking a systematic exploration of the internal adaptive mechanisms and resilience of these landscapes. This study situates oasis gardens within the theoretical framework of resilient landscapes and cultural landscapes to deeply analyze the inherent logic and practical pathways of their construction wisdom, aiming to provide historical insights and theoretical support for contemporary ecological development and cultural sustainability in arid regions.
[Methods] This research follows a methodological pathway of “data collection, feature induction, overlay analysis, and wisdom extraction.” First, in the phase of data collection and feature induction, historical records from various periods concerning oasis gardens were compiled to summarize their construction history, functional requirements, and resilience evolution. Based on documents such as the Integration of the Third National Cultural Relics Census of Xinjiang Uygur Autonomous Region and Immovable Cultural Relics, information including names, periods, and locations of 92 garden samples was extracted to establish a spatiotemporal database, analyzing their spatial distribution and construction patterns to support the study of landscape resilience and cultural stratification. Field mapping of 33 existing residential sites and one manor was conducted to document the evolution of the relationship between dwellings and courtyards, spatial typologies, and other aspects, deepening the understanding of garden construction mechanisms. Second, in the phase of overlay analysis: DEM data within the basin were extracted to generate contour lines, which were overlaid with geographical elements such as hydrographic networks and streets to create base maps. The 92 garden samples were plotted onto current maps to achieve spatial quantification and visualization of construction features. The Kernel Density tool was used to generate a kernel density analysis map, revealing the spatial aggregation and distribution patterns of the gardens. Third, utilizing the theories of resilient landscapes and cultural landscapes, the evolution and characteristics were interpreted to extract the inherent construction wisdom of the oasis gardens.
[Results] First, the construction and succession of oasis gardens are the result of the synergistic effects of environmental, economic, and cultural factors. The core of this process lies in maintaining a dynamic balance among the utilization of natural resources, the fulfillment of construction demands, and the inheritance of historical and cultural heritage. Second, under extreme drought and sandstorm conditions, the construction elements of various types of oasis gardens exhibit diversity and integration. Common elements such as rivers, settlements, oases, vegetation, and landforms constitute the foundational base for systemic resilience. The spatial pattern demonstrates characteristics of “water-system dependence, settlement symbiosis, and landform adaptation.” Third, the construction wisdom is reflected in a four-dimensional collaborative mechanism: “environmental borrowing, ecological adjustment, dynamic adaptation, and regional translation.” This mechanism aligns with the “absorption-adaptation-transformation” capacity of resilient landscape and the “stratification” characteristic of cultural landscapes, effectively maintaining the sustainability of the human-land system in an extremely arid environment. Environmental borrowing relies on the absorption capacity of resilient landscapes to seek benefits and avoid harm through spatial cognition. Ecological adjustment corresponds to the buffering and regulating capacity, actively adapting to the environment through measures such as controlling architectural forms, optimizing shape coefficient, and utilizing walls, plants, open corridors, and pergolas for shading. Dynamic adaptation involves adjustments based on climatic seasons, reflecting the cyclical “release-reorganization” process in resilience theory, reconstructing resources through time-varying strategies to meet new demands. Regional translation represents the creative transformation of environmental constraints and local knowledge, with regional expressions such as the Ayiwang residence, the eave corridor, the high-shed frame enhancing the system's capacity for reorganization and transformation at the cultural level.
[Conclusion] Viewed through the dual theoretical lenses of resilient landscapes and cultural landscapes, this study yields the following conclusions and insights. First, ancient practitioners accumulated extensive experience in oasis garden construction by balancing natural resource utilization, construction needs, and cultural heritage under extreme aridity and sandstorms, offering significant reference value for sustainable landscape development in contemporary arid regions. Second, the construction wisdom of oasis gardens is essentially an adaptive design and resilience system based on local knowledge and following the path of “environmental borrowing, ecological adjustment, dynamic adaptation, and regional translation.” This mechanism not only effectively copes with environmental stress but also accumulates profound cultural landscape value through long-term human-land interaction. Third, corresponding practical insights are proposed for the four-dimensional mechanism: at the level of environmental borrowing, a nested protection pattern should be established, making benefit-seeking and harm-avoidance the core of ecological planning; at the level of ecological adjustment, promoting a composite ecological model integrating “ecological-production-living” functions and local suitable technologies; at the level of dynamic adaptation, implementing the principle of flexible planning to enhance systemic adaptability; at the level of regional translation, focusing on revitalizing cultural carriers to facilitate the contemporary transformation of traditional wisdom. The construction wisdom of the oasis gardens in the Tarim River Basin embodies a holistic ecological worldview of human−nature coexistence and holds significant implications for sustainable landscape planning in arid regions globally.
