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Rapid industrialization and urbanization in canal areas have led to significant conversion in production-living-ecological space (PLES), yielding short-term social-economic benefits but causing serious ecological degradation. However, the complex and dynamic interactions between PLES and ecosystem function remain underexplored, despite their importance for guiding sustainable canal development. Therefore, we analyzed the dynamic changes in PLES and ecosystem service value (ESV) in the Jiangsu section of the Beijing-Hangzhou Grand Canal, along with their interrelationships. By optimizing the ESV evaluation model to incorporate natural, social, and economic factors, we examined the spatiotemporal evolution of PLES and ESV from 2000 to 2020. Finally, we quantified the dynamic response of ESV to PLES using contribution rate factors and identified trade-offs and synergies among ESV indicators. Over the past two decades, ecological space (ES) expanded by only 5.31 %, yet contributing 94.36 % of total ESV growth. Despite fluctuations during 2005–2010, synergies among various ESV types remained largely stable. The regulation service shows the most significant response to the conversion of PLES, with an increase in ES’s ESV of CNY 67.87 billion over 20 years, representing 75.34 % of total ESV growth. Notably, the hydrologic regulation contributes substantially, with an increase in ES’s ESV of CNY 60.87 billion, accounting for 67.57 % of total ESV growth. Our findings provide a scientific basis for the sustainable development and resource management in canal areas.

Hills and mountains cover approximately 25 % of Earth’s landmass; therefore, investigating landscape ecological risk (LER) in these regions is imperative for ecosystem management. Hilly and mountainous regions susceptible to influences such as desertification and erosion include the Southern Hill and Mountainous Belt (SHMB) in southern China. Over the past 30 years, the SHMB has undergone significant changes, offering an excellent research case. A comprehensive assessment of the ecological status of this region is crucial for the protection and management of the ecosystems in the SHMB. This study assessed the LER of the SHMB, identified influencing factors over the past 30 years, and utilized a patch-generating land-use simulation model (PLUS) to project future land use and LER. Accounting for more than 90 % of the total area, cropland and forestland were the two most common land use types in the SHMB. From 1990 to 2020, impervious surface and water area saw obvious increases, rising by 154 % (from 1209.37 km2 to 3073.59 km2) and 21 % (from 1584.78 km2 to 1924.8 km2), respectively. Grasslands and shrublands decreased by 54 % and 34 %. It is anticipated that there will be little change in land-use types by 2030 compared to 2020. Additionally, the overall LER in the SHMB was low, with low- and medium–low-risk representing around 70 % of the overall risk. The general state of LER improved during the research period but did not converge. Specifically, the LER intensity did not decrease although the total LER showed a declining trend. In the western portion of the research region, the karst area displayed an increasing LER, and the severity of the high-risk area increased. Furthermore, natural factors promote the restoration of LER. For example, the abundance of hydrothermal conditions (i.e., increased temperature and precipitation) promotes the recovery of vegetation growth and reduces the LER. Human activities, such as the construction of stations, highways, and an increasing population, exacerbate LER, contributing to an increase in LER. This study offers helpful guidance for formulating ecological conservation strategies to maintain the ecological balance and sustainability of hilly and mountainous regions.

Ecosystem services and ecological risk prevention are important factors that influence for sustainable socio-economic development. In recent years, fewer studies, and practices have been conducted on the value of ecosystem services and ecological risk management in larger regions, and the mechanisms of their interactions have not been adequately investigated. The central southern region of China is in a stage of high-quality development, and Hunan Province in this region is used as an example to investigate the interaction mechanism between ecosystem service value (ESV) and landscape ecological risk (LER)as well as to generate new ideas for coordinated and sustainable regional socioeconomic development. This study developed an evaluation model of ESV and LER by synthesizing multi-source data of Hunan Province from 1990 to 2020 and further revealed the interaction mechanism between ESV and LER. We found the following: (1) Hunan Province experienced rapid urbanization, and both ESV and LER showed increasing trends. A complex and significant positive correlation was observed between these two variables. (2) The ESV in Hunan Province showed an overall increasing trend from 1990 to 2020, and each level of ESV was distributed from high to low, with the core of the high value area spreading outward. ESV gradually decreased after 2010, when urban expansion was rapid. (3) The LER level in Hunan Province shifted from medium-low risk to high risk, the risk level gradually increased, and the overall distribution pattern of each level was high in the north and south and low in the surroundings. (4) There were four types of spatial correlations at the local scale: high value and high risk, high value and low risk, low value and high risk, and low value and low risk. Based on these results, an ecological risk prevention zoning plan was developed for Hunan Province. This study contributes to understanding of the interactive and synergistic relationship between ESV and LER in Hunan Province, which is critical for optimizing sustainable economic and social development.

Coupling land use and climate change under shared socioeconomic pathway and representative concentration pathway (SSP–RCP) scenarios can provide more accurate predictions of water supply risks, thereby supporting decision-making for spatial planning with a focus on climate adaptation. Climate change exhibits spatial and temporal differences. To meet the requirements of spatial planning, further research is needed to assess water supply risks at different basin or regional scales. In this study, we selected four SSP–RCP scenarios for analysis, considering the temporal scale of spatial planning. The climate modeling capabilities of five global climate models (GCMs) and a multi-model ensemble (MME) were evaluated using a Taylor diagram, which assesses the performance of climate element simulations. The modeling framework that consisted of system dynamics (SD), patch-generating land-use simulations (PLUS), and Soil and Water Assessment Tool (SWAT) was employed to analyze synergistic changes in climate, land use, and water supply. The Ganjiang River Basin (GRB) serves as a case study for climate-adaptive planning at the basin scale, given its characteristics of high agricultural water demand and vulnerability to droughts and floods. The study aims to provide decision-making support for such planning. In our projections, precipitation in the GRB showed a slightly increasing trend from 2021 to 2050. Monthly precipitation increases during the flood season in August and decreases during the dry season from October to December. The maximum and minimum temperatures showed an increasing trend on both the yearly and monthly scales, with slightly higher increases during fall and winter. During the planning phase, the land use quantities of SSP126 and SSP245 showed similar variations. SSP370 experienced the most significant reduction in farmland, while SSP585 displayed a more scattered and punctuated layout of construction land. The annual water supply in the GRB showed a slightly decreasing trend from 2021 to 2035 and 2036–2050, and the largest reduction was found in SSP370. The trend of variation in the monthly water supply was complex. There was a consistent trend of decreasing water supply during the dry season, whereas the changes during the flood season were more complex. Seasonal variations in water supply are a major water security concern for the basin’s future. It is necessary to strengthen the agricultural water security planning in the northern region of the basin and enhance its ability to adapt to droughts and floods.

Spatial heterogeneity of human activities (SHHA) is part of the heterogeneity of urban ecosystems, which influences the understanding of ecological processes and landscape functions. Few ecological security pattern (ESP) studies have comprehensively measured SHHA and explicitly explained its effect on ESP planning. It affects the efficiency and landscape functions of ESP planning, leading to challenges in maximizing urban development and ecosystem benefits. In this study, Tencent user density (TUD) data considering human activity for all time periods and point of interest (POI) density with fine-scale human activity location information were fused by using wavelet transform as the spatial distribution of human activities. We applied it to correct the resistance surface for ESP planning, then proposed targeted restoration and conservation policies at a fine scale by combining human activities and POIs. The results revealed that the corrected resistance surface could approach the heterogeneous megacity for spatial and functional structures. More importantly, ESP planning based on the corrected resistance surface could enhance efficiency and landscape functions. This research strengthens our understanding of the effect of SHHA on ESP planning. It may provide important insights for policymakers concerning integrated human-natural systems in landscape planning.

Land use and land cover change (LUCC) has yielded significant impacts on ecosystem structure and functions. Gross primary production (GPP), the largest flux in the terrestrial carbon cycle, has been drastically changed by various LUCC activities. However, the indirect impacts of LUCC on GPP (i.e., local environment changes induced by LUCC), particularly those related to landscape dynamics, remain unclear. Here, we explored the relationships between GPP and landscape metrics of forest ecosystems in China along a forest coverage gradient from 2001 to 2019, using an up-to-date GPP dataset derived from Solar-Induced Chlorophyll Fluorescence and a widely used landcover product MCD12Q1. Results showed that forest landscape features (e.g., core area index, CAI) synchronized with GPP spatially as shown by the distribution of their hot/cold spots on correlations. Furthermore, two nonlinear change patterns of GPP and landscape metrics along forest coverage gradient were found. One is a hump-shaped pattern, which indicated that GPP and some landscape features (e.g., annual median GPP, annual change rate of forest composition) peaked in medium (about 70–80%) forest-cover regions. Another is a super-linear curve, revealing the rapid and accelerated growth of some landscape features (e.g., annual median CAI) in high forest-cover regions. Finally, forest coverage affected the sensitivity of GPP to landscape features in a nonlinear fashion, characterized as an inverted ‘hook’ curve peaking in intermediate (around 70%) forest-coverage regions. Our study proposed the optimal landscape regulation hypothesis to explain the nonlinear pattern: forest GPP is most responsive to the landscape pattern regulation at intermediate to low levels of disturbance, implying that forest coverage has various impacts on landscape features; together they affect GPP nonlinearly. Regulating the forest landscape composition and configuration can enhance the performance of forest ecosystems in addition to managing forest coverage. Thus, we recommend the adoption of suitable region-specific forest management practices to improve GPP and other ecosystem services of forest ecosystems via manipulating landscape composition and configuration.

Ecosystem services (ES) are directly affected by land use and land cover changes (LUCC); however, the impacts of extended period LUCC on ES are poorly explored. Here, we mapped the 1998–2019 annual land use and land cover in the Dongting Lake Region (China) and explored the spatiotemporal evolution of LUCC and landscape patterns (i.e., composition, shape, and aggregation) and their relationship with ES, including carbon storage, gross primary production (GPP), water conservation capacity, and crop yield in the region. The results showed a significant increase in forest areas and impervious surfaces and a decrease in croplands and bare lands with spatial heterogeneity. Carbon storage was strongly correlated with forest, cropland, waterbody, impervious surface, and bare land, and there was a nonlinear relationship between landscape patterns and ES. The trade-offs and synergies (correlations) among ES varied considerably, with crop yield being significantly synergistic with carbon stocks, GPP, or GPP with carbon stocks. This study revealed the nonlinear relationship between landscape patterns and ES, and the mechanism of landscape characteristics on ES. The findings can provide scientific support for regional land use planning, ES regulation, and landscape optimization in the lake region.

The division of the territorial space functional area is the primary method to study the rational exploitation and use of land space. The research on the Production–Living–Ecological Space (PLES) change and its motivating factors has major implications for managing and optimizing spatial planning and may open up a new research direction for inquiries into environmental change on a global scale. In this study, the transfer matrix and landscape pattern index methods were used to analyze the temporal changes as well as the evolution features of the landscape pattern of the PLES in the Chaohu Lake Basin from 2000 to 2020. Using principal component analysis and grey correlation analysis, the primary driving indicators of the spatial changes of the PLES in the Chaohu Lake Basin and the degree of the influence of various driving factors on various spatial types were determined. The study concluded with a few findings. First, from the standpoint of landscape structure, the Chaohu Lake Basin’s agricultural production space (APS) makes up more than 60% of the total area, and it and urban living space (ULS) are the two most visible spatial categories. Second, the pattern of the landscape demonstrates that the area used for agricultural production holds a significant advantage within the overall structure of the landscape. Although there is less connectedness between different landscape types, less landscape dominance, and more landscape fragmentation, the structure of different landscape types tends to be more varied. Third, the findings of the driving analysis demonstrate that the natural climate, population structure of agricultural development, and industrial structure of economic development are the three driving indicators of the change of the PLES. Finally, in order to promote the formation of a territorial space development pattern with intensive and efficient production space, appropriate living space, and beautiful ecological space, it is proposed to carry out land regulation according to natural factors, economic development, national policies, and other actual conditions.

Currently, people pay more and more attention to their own health condition, and have shifted from the traditional passive participation in sports to the active participation, which brings the national sports boom is more and more intense. In this paper, we believe that the landscape design of sports scenes should take into account the needs of the public's life and the development trend of changing from landscape form to focus on the harmonious relationship between the human body and the environment, and try to put forward the form of sports landscape in the field of landscape design of sports scenes, and combined with the personalized feedback technology to design an ideal sports landscape design program with a high degree of perception to do a preliminary investigation. This requires designers to provide personalized feedback services, so this paper introduces user interest subclasses, analyses the user's historical behavioral operations, obtains the user's rating value on the interest subclasses, and then calculates the user's interest distribution based on the rating value. Based on the idea of user interest subclasses, considering the local similarity of users, we spread the traditional collaborative filtering algorithm to different interest subclasses for the prediction of overall similarity calculation and rating. Then we combine the calculation results with the user's interest distribution to obtain the final recommendation list of the user. Based on the personalized feedback technology in the sports scene landscape design provides a new perspective and way of thinking, and we hope that the sports scene landscape can bring people a pleasant sports experience, but also can call on more people to strengthen the importance of sports and fitness. [ABSTRACT FROM AUTHOR]