The health status of ecosystems is an important prerequisite for ensuring regional ecological security. Exploring the spatiotemporal patterns, driving mechanisms, and zoning regulation pathways of ecosystem health is of great significance for achieving co-ordinated and sustainable regional ecosystems. This study uses China as a case area and applies the InVEST model to measure integrated ecosystem services and incorporates it into an evaluation framework for ecosystem health based on the “Vigor-Organization-Resilience-Ecosystem Services” (VORS) model. It reveals the spatiotemporal evolution characteristics of ecosystem health in China from 2000 to 2020 and employs the geodetector and spatiotemporal geographically weighted regression model to analyze the main influencing factors and spatial differentiation characteristics, thereby exploring ecological management zoning and optimization pathways. The study results show that (1) during the study period, the overall ecosystem health level in China showed a declining trend, dropping from 0.397 in 2000 to 0.377 in 2020. (2) Overall, China’s ecosystem health exhibits strong spatial positive correlation and spatial clustering characteristics, with a basic pattern of lower values in the northwest and higher values in the southeast. (3) Vegetation coverage, population density, density of road network, and per capita GDP are the main influencing factors of ecosystem health in China. (4) China is divided into five types of Ecological Management Zones: Ecological Conservation Zone, Ecological Enhancement Zone, Ecological Buffer Zone, Ecological Remediation Zone, and Ecological Reshaping Zone, with differentiated strategies proposed for optimizing ecosystem health in each zone.

This research delves into the spatial and temporal evolution characteristics of rural areas, focusing on understanding the phenomenon of rural hollowing in Fujian Province and other coastal regions. By analyzing data from the Fujian Province Statistical Yearbook and the Social Development and National Economy Statistical Bulletin (2010–2020), employing methodologies such as Pearson correlation and the natural interruption point method in ArcGIS, this study seeks to provide both theoretical and practical groundwork for rural revitalization efforts. The findings of this study yield significant insights. Firstly, a pronounced geographical differentiation emerges in the context of rural hollowing in Fujian province, characterized by a distinctive “high inland and low coastal” spatial pattern. Secondly, despite its coastal location, Fujian Province continues to confront substantial rural hollowing challenges. Although the overall pace of rural hollowing development has been moderate, the persistence of population and economic hollowing is noteworthy. Consequently, the issues of depopulation and economic decline in rural areas remain pressing concerns for Fujian Province. Lastly, the investigation identifies key driving forces behind the phenomenon of rural hollowing, encompassing factors such as arable land area, rural population settlement rate, economic development level, and farmers’ net income. These drivers significantly influence the dynamics of rural hollowing. Drawing from the research findings, this study proposes several strategic recommendations to counteract rural hollowing in coastal regions. These include tailoring management approaches to address geographical disparities, enhancing resource allocation and land utilization practices, orchestrating shifts in industrial structure to foster integrated urban–rural development, and emphasizing the revitalization of talent to sustain the progress of rural areas.

The water–energy–food (WEF) system acts as a critical nexus of social–ecological systems. However, rapid urbanization has intensified the regional imbalance in the supply and demand of ecosystem services (ESs). Clarifying the spatiotemporal matching of ecosystem services supply and demand (ESSD) within the WEF framework and revealing the driving mechanisms behind such imbalances are essential to formulating reasonable zoning schemes and targeted optimization strategies for the coordinated development of the regional WEF system. Taking Zhejiang Province as a case study, this research uses water yield (WY), carbon sequestration (CS), and grain production (GP) to characterize the WEF nexus system. It uses the InVEST model to assess WY and CS, applies spatial allocation methods to characterize GP, and integrates socioeconomic data to quantify the demand for the above three ESs. All indicators were standardized and integrated with equal weights to further clarify the comprehensive levels of ESSD. By integrating the Geodetector and K-Means clustering methods, the study analyzes the supply–demand matching of ecosystem services and its driving mechanisms in Zhejiang Province during this period, thereby exploring ecological management zoning and optimization strategies within the WEF system. The study findings indicate that: (1) From the supply perspective, Zhejiang Province’s WY services demonstrate a trend of elevated activity in the southwest and diminished presence in the northeast; high values for CS services are predominantly found in the vegetation-rich areas of the northwest, while high values for GP services are clustered in the northern Zhejiang Plain; from the demand perspective, high values for all three ESs in Zhejiang Province are primarily located in economically active, densely populated urban areas. (2) The correlation between ESSD within Zhejiang Province’s WEF system exhibits significant spatial heterogeneity and is driven by the combined effects of natural and socioeconomic factors, with the interaction between these two factors often producing a synergistic effect. Specifically, annual average precipitation and population density are the dominant factors influencing WY services, NDVI and human footprint are the dominant factors influencing CS services, and population density and GDP are the dominant factors influencing GP services. (3) From 2000 to 2020, the supply–demand ratio for comprehensive ESs in Zhejiang Province generally followed a pattern of being lower in the east and higher in the west. The supply–demand imbalance of ESs intensified in the core areas of eastern cities, whereas the western regions maintained a relatively sound supply–demand balance. (4) The study classifies the counties in Zhejiang Province into four ecological management zones—ecological stable zones, ecological conservation zones, ecological control zones, and ecological restoration zones—and explores differentiated approaches to optimizing these zones and implementing control strategies.

Exploring the relationship between regional ecosystem service supply and demand and establishing refined ecological management zoning can help enhance the rational allocation and conservation capacity of ecosystem services. Taking Anxi County as the study area, this study integrates the InVEST model, a supply-demand matching index, and the XGBoost-SHAP method to examine the spatiotemporal characteristics and driving mechanisms of ecosystem service supply-demand matching from 2000 to 2020 and to delineate ecological management zones from a combined dynamic-static perspective. The results indicate that: (1) From 2000 to 2020, the supply of multiple ecosystem services in Anxi County generally exhibited a spatial pattern of higher levels in the west and lower levels in the east. Among them, the supply of water yield and soil retention first decreased and then increased, whereas habitat quality and carbon storage generally declined to varying degrees. Demand for all four ecosystem services increased to varying degrees. (2) From 2000 to 2020, the mean values of the four ecosystem service supply-demand ratios in Anxi County declined to varying degrees. Among them, the supply-demand ratios of habitat quality (HQ), carbon sequestration (CS), and water yield (WY) generally exhibited a spatial pattern of higher values in the west and lower values in the east, whereas the soil retention (SR) supply-demand ratio showed an opposite pattern with higher values in the east and lower values in the west. (3) The nighttime light index, elevation, GDP density, and mean annual temperature were the core variables influencing the integrated ecosystem service supply–demand matching, with the nighttime light index contributing the most; GDP density and population density generally showed negative effects, whereas elevation, NDVI, and mean annual precipitation exhibited positive effects to varying degrees. Significant nonlinear and interactive effects were observed among the driving factors. (4) At the village scale, Anxi County is divided into three ecological management zones, agricultural production zones, resilient development zones, and ecological conservation zones with differentiated management strategies implemented. This study improves the rationality and efficiency of regional resource allocation and provides a scientific basis for local governments to formulate ecological protection policies, strengthen ecological security, and implement ecological compensation mechanisms.

Investigating the spatiotemporal distribution patterns of regional ecosystem health and the methods for optimizing their zoning is essential for enhancing ecosystem management and sustainable development. This study takes Fujian Province, a pivotal forest region in southern China, as the research object to establish a county-level ecosystem health evaluation framework grounded in the vitality–organization–resilience–ecosystem (VORS) model. It further conducts a comprehensive spatial–temporal analysis of ecosystem health dynamics from 2000 to 2020 and explores ecological management zoning and optimization strategies. The results indicate that (1) from 2000 to 2020, the overall ecosystem health level in Fujian Province maintained a relatively high status and exhibited a steady upward trajectory, with the index rising from 0.4694 in 2000 to 0.4762 in 2010, and further increasing to 0.4865 in 2020. (2) The health of ecosystems in Fujian exhibits significant geographical autocorrelation and aggregation, characterized mostly by high–high and low–low clusters. Typically, it has a geographical distribution characterized by elevated values in the northwest and diminished values in the southeast. (3) In light of the present condition and temporal dynamics of ecosystem health, the study classifies Fujian’s counties into three ecological management categories—conservation, stabilization, and reshaping zones—and puts forward tailored optimization measures for each region. The methodology employed in this study provides a general framework for ecosystem health assessment, which can offer useful references and insights for forest ecosystem health evaluation and refined, zone-specific ecological management in forest regions.