Urban greenways are pivotal in enriching urban quality and fostering socio-ecological sustainability. Previous studies on urban greenway networks have often overlooked user-based experience efficiency, leading to the underutilization and insufficient translation of cultural services into human well-being. In this study, we introduce a user behavior-driven assessment framework for planning multifunctional urban greenways that connect parks with high green space exposure and maximize recreational mobility. Beijing’s built-up urban areas (BBUA) were selected as the case study area. Firstly, we evaluated the green space exposure of 331 parks in BBUA using an integrated “Availability–Accessibility–Adaptability” assessment framework as potential carriers. Then, through spatially explicit workflows and the least-cost path methodology, we leveraged a vast dataset of 70 million public transportation swipe records to optimize the alignment of multifunctional greenways, prioritizing the criterion of maximizing recreational footfalls. The results showed that the potential greenways network spans 1566.36 km in BBUA, encompassing 93.88% of parks and offering six diverse functions. It can serve 34.39–35.92% of bus recreation passengers, with this ratio tending to be higher on weekends. However, we identified obstacle points (non-greenway sections) in the networks based on residents’ view perceptions and panoramic street images, primarily located in densely built-up central areas and along southern trunk roads. By addressing these disconnections, the integrity and connectivity of urban greenway networks in BBUA will be improved. Overall, the framework we present can be used to construct greenway networks that maximize the perceived accessibility for bus-based visitors, with valuable implications for sustainable urban planning and regeneration initiatives.

Many single-land-use simulation models are available to simulate and predict Land Use and Land Cover Change (LUCC). However, few studies have used multiple models to simulate LUCC in the same region. The paper utilizes the CA-Markov model, Land Change Modeler (LCM), and Patch-generating Land Use Simulation model (PLUS) with natural and social driving factors to simulate the LUCC on the Western Sichuan Plateau, using Kappa coefficient, overall accuracy (OA), and Figure of Merit (FoM) to verify the accuracy of the model, and selects a suitable model to predict the LUCC and landscape pattern in the study area from 2020 to 2070. The results are as follows: (1) The LCM has the highest simulation effect, and its Kappa coefficient, OA, and FoM are higher than the other two models. (2) The area of land types other than grassland and wetland will increase from 2020 to 2070. Among them, the grassland area will decrease, but is still most prominent land category in this region. The proportion of wetland areas remains unchanged. The fragmentation degree of forest (F), grassland (GL), shrubland (SL), water bodies (WBs), bare areas (BAs), and permanent ice and snow (PIS) decreases, and the distribution shows a trend of aggregation. The dominance of F and C decreases but still dominates in the landscape. The overall landscape aggregation increased and complexity decreased, and each landscape type’s diversity, evenness, and richness increased, presenting as a more reasonable development. Using multiple models to simulate the LUCC in the same region, and choosing the most suitable local land model is of great significance to scientifically manage and effectively allocate the land resources in the field.

Land use change significantly influences landscape pattern adjustments, thereby altering ecosystem functions and service flows, ultimately impacting ecosystem service value (ESV). However, previous studies have often examined the impacts of land use change and landscape patterns on ecosystem services from a one-dimensional perspective, overlooking the complex interactions among these factors. This study proposes a “process–structure–value” response framework and applies it to a case study of the western Sichuan urban agglomeration. Its aim is to identify the spatial and temporal characteristics of land use and landscape pattern evolution. Additionally, it quantitatively evaluates the synergistic effects of these changes on ESV evolution from 2000 to 2020 using a correlation analysis. The results show that, over the past 20 years, the study area experienced a significant expansion of construction land by 184,729.41 hm², leading to the dispersion and fragmentation of arable land, grassland, and waters, resulting in an overall trend of fragmentation and diversification in landscape patterns. The ESV increased by CNY 2.619 billion, primarily due to the increased ESV associated with forest land and waters. This study found that the synergistic effects of land use processes and landscape pattern structures significantly enhanced ESV. The transition from construction land and arable land to forest land and waters notably improved the ESV. Meanwhile, increased landscape diversity and patch connectivity further enhanced the ecosystem service function. Furthermore, the ecological environment of the study area remained vulnerable despite the increased ESV. Overall, the results highlight the significant correlation between changes in land use processes, landscape patterns, and ESV, emphasizing the necessity of integrating the “process–structure–value” framework in future research to comprehensively assess the responses of land use and landscape patterns to ESV, providing a more comprehensive reference for land use planning and policy development.

The ecological resilience of forests is the ability to return to a stable state after being subjected to external disturbances, and it is among the critical indicators of forest status. Climate change has significant effects on forest ecological resilience and diversity. In this research, we selected Mao County as the study region, and employed the forest landscape model LANDIS-II to simulate the effect of different climate scenarios on the ecological resilience of alpine forests in western Sichuan during the next 300 years from the forest composition and structure perspective. The findings revealed that: (1) climate change will favor an increase in forest ecological resilience values in short simulations, but future climate scenarios will negatively impact the ecological resilience of forests as the simulation progresses through the middle and long term. (2) The rate of change of forest ecological resilience in the MTDF and SCF ecotones, which have a higher proportion of Fir (Abies fabri) and Spruce (Picea asperata), was greater than that in the rest of the ecotones in the short-term simulation. In contrast, it was the opposite in the medium-term simulation. The rate of change of forest ecological resilience was more significant in the long-term simulation in all four ecotones. (3) The high values of forest ecological resilience in the short- and medium-term simulations were primarily concentrated within the MTDF and SCF ecotones among the midwestern and northern parts of the study region. When the simulation proceeded to a later stage, the ecological resilience of the forests decreased significantly throughout the study region, with high values occurring only in some areas within the western parts of the study region. The research results can grasp the influence of future climate on the ecological resilience of high mountain forests within western Sichuan and provide an essential reference for the sustainable development of local forests.

Constructing regional ecological security patterns (ESP) and enhancing carbon sequestration are essential for achieving China’s dual-carbon goals. However, rapid urbanization has intensified landscape fragmentation, disrupted ecosystem flows, and significantly altered urban ecological networks, weakening their carbon sink functions. Using the Chengdu metropolitan area (CMA) as a case study, a time-series ESP from 2000 to 2020 was constructed. Morphological Spatial Pattern Analysis (MSPA), the Minimum Cumulative Resistance (MCR) model, the gravity model, and complex network theory were employed to assess the spatiotemporal evolution and carbon sequestration capacity of the ecological network. Results revealed continuous declines in ecological sources and corridors, an initial rise then stabilization in resistance, and weakening connectivity, particularly in central and western subregions. Reductions in modularity and topological indices reflected lower ecological stability and greater vulnerability. Forest land served as the primary carbon sink, closely associated with multiple topological metrics; grassland sequestration correlated with clustering, while water bodies were positively linked to centrality measures. Adding 10 stepping-stone nodes and 45 corridors could enhance carbon sequestration by approximately 4156 Mg C yr⁻¹, with forests contributing 94.8% by 2020. This study provides scientific support for resilient regional ESP construction and dual-carbon strategy advancement.

The cultivation industry occupies a large proportion of greenhouse gas emissions in agriculture. Assessing greenhouse gas emissions from the cultivation industry is pivotal for mitigating emissions and promoting sustainable cultivation. Utilizing greenhouse gas emission calculation methods recommended by the Intergovernmental Panel on Climate Change (IPCC) and other methods, this work evaluated annual emissions and the emission structure of major crops from 2005 to 2021 in the Chengdu Plain, a significant agricultural region in Southwest China. We identified nitrogen fertilizer as the primary contributing factor to high emissions from cultivation production. Subsequently, we analyzed the trend and utilization of nitrogen fertilizer, which proposes essential strategies for reducing greenhouse gas emissions. The results showed that greenhouse gas (GHG) emissions from the cultivation industry in the Chengdu Plain exhibited a growth, fluctuation, and eventual decline trend from 2005 to 2021. The emissions increased from 5,148,900 t in 2005 to 6,289,700 t in 2009, representing a 22.16% increase, and subsequently decreased to 5,109,900 t in 2021, marking a 23.31% decrease. Nitrogen fertilizer application emerges as the primary source of GHG emissions, constituting approximately half of the total, with nitrogen fertilizer manufacturing contributing significantly as well, collectively amounting to about 70%. We also found that the proportion of greenhouse gas emissions attributed to cash crop cultivation has gradually increased over the last decade. Among these crops, vegetables exhibit the highest emissions, comprising nearly half of the total emissions from 2019 onwards. However, the nitrogen fertilizer use efficiency of cash crops is less than 30%, with higher nitrogen surplus, ammonia volatilization, and nitrogen leaching per unit area, and the total amount is higher than that of grain crops. Among cash crops, vegetables exhibit the highest amount of nitrogen surplus, ammonia volatilization, and nitrogen leaching, constituting nearly half of the total amount in the study area since 2019. Our findings significantly affect sustainable and low-carbon cultivation industry development in the study area.