4. Discussion

4.1 Spatial and temporal heterogeneity of EHI and UI from 2000 to 2020

4.1.1 UI dynamics from 2000 to 2020

China has experienced rapid urbanization in population, economy, space and society, and the urbanization levels among cities and regions varied spatially and temporally (Fig 3 and Fig 5). China’s population change has entered a period dominated by the population’s spatial distribution (Cheng, 2021). Population movement presents two theoretical modes, that is, nearby urbanization and remote urbanization. Currently, the primary means by which rural residents transition to urban residents is through remote urbanization, facilitated by significant population mobility (Zhang, 2022). This process changed the ratio of non-agricultural population and population density in the inflow and outflow areas, resulting in the spatial and temporal differentiations of the regional population urbanization (Fig 3). In a sense, increased population urbanization level in central and eastern cities reflects their increased economic and social dynamics.
Large-scale population movements have brought abundant labor force for economic growth and industrialization. Cities with innate geographical advantages developed preferentially (Chen, 2014). They offered higher productivities because of scale effects and agglomeration economies (Henderson, 2002), with the eastern coastal cities and provincial capitals remarkably in the early stage. Accordingly, resources were tilted to these areas, gradually widening the gap with northwest and southwest. Meanwhile, cities adjacent to higher economic levels were affected by diffusion effect, and improved their economic urbanization levels (He and Zhou, 2019). However, this effect was only manifested in cities east of the Hu Line, and behaved a weak driving effect on the economy of the west. Under the implementation of the National Western Development Strategies, although western economic level has raised significantly, it still lags far behind the eastern region.
Spatial rural-urban land transformation is an inexhaustible driving force for economic development, with a profound influence on economic growth (Qu, 2018). Spatial urbanization is mainly driven by the agglomeration of major shares of population and economic output in central and eastern regions. Furthermore, policy factors play a crucial role in coordinating regional spatial differences. In the early stages of urbanization, the eastern and central regions received more financial support than the western regions (Li and Zou, 2021). With urbanization entering a quality improvement phase, land supply was prioritized over western regions, and more construction land quotas were allocated to western regions (Wang, 2022).
Social urbanization levels revealed a steady growth trend, which largely depended on economic growth. China’s rapid economic development has boosted the income levels and living standards of urban residents, contributing to the rise of domestic consumption. By comparing the historical data of total retail sales of social consumer goods and GDP, changes in consumption were basically in line with economic fluctuation trend. This explained why some cities with high economic development levels behaved high social urbanization levels, which were mainly distributed in central and east (Fig 3). Urbanization expands consumer demand through agglomeration and scale effects (Henderson, 2005). The promotion and balanced development of social urbanization is a continuous and slow process, during which population mobility, economic growth and spatial expansion provide the material basis.

4.1.2 EHI dynamics from 2000 to 2020

Terrestrial ecosystem health and various indicators revealed significant spatial and temporal heterogeneity (Fig 6). Regions in south and northeast exhibited better health than the central, and the west behaved poor health. Ecosystem vigor and resilience showed similar distributions to EHI, suggesting that land use changes and vegetation cover played an crucial role in ecosystem health during the study period. The research of Xie (2021) also proposed that vigor was the most basic condition to determine ecosystem health status. Forestland coverage is crucial to vigor and resilience indicators, and ecosystem vigor is usually high in areas with high vegetation cover (Li and Xie, 2021). According to the 9th China Forest Inventory (https://forest.ckcest.cn/sd/si/zgslzy.html), most of the top 10 provinces in forest cover were in southern China, with Fujian Province ranking the first for the last five years with a coverage rate of over 60%. Provinces such as Jiangxi, Guangxi, Zhejiang, Hainan, Yunnan, and Guangdong also had forest cover rates around 60%. Although the values of the three northeastern provinces was around 40%, they were much higher than central and western regions. Moreover, grassland, arable land and water bodies also exhibited higher ecosystem resilience in addition to forestlands.
Since the 21st century, however, a large amount of wetland and agricultural land has been encroached by urban build-up expansion. This process resulted in severe landscape fragmentation, which in turn directly resulted in low NDVI and ecosystem organization (Peng, 2015; He, 2019; Li, 2021). Studies have shown that terrestrial ecosystem health in the core areas of urban agglomerations was poor, as well as in the neighboring cities (Chen and Zhao, 2022). This indicates a significant spatial dependence of ecosystem health levels, which is also presented in our findings. Before the new-type urbanization construction, China implemented a resource-driven economic development strategy, resulting in significant spatial spillover effects and negative externalities of environmental pollution on ecosystem health (Xiao, 2019). Several typical ecologically fragile areas in the central and western regions, such as the Loess Plateau, the Southwest Mountains, and the Qinghai-Tibet Plateau, exhibited fragile ecological environments and weak ecosystem health levels (Xie, 2021). In particular, the Qinghai-Tibet Plateau and Northwest China with weak vegetation productivity and low vegetation coverage presented relatively drastic variations due to high altitude, scarce precipitation, arid climate, and poor soil (Xie, 2021; Shi, 2021). The management of these areas is still focused on protection and restoration, but the ecological corridors should be strengthened to avoid the “island effect” of protected areas (Yang and Song, 2020).

4.2 The tie between ecosystem health and urbanization

Urbanization and terrestrial ecosystem health indicated a negative relationship, and revealed local spatial aggregation (Fig 9). Terrestrial ecosystem health was strongly influenced by urbanization in eastern cities. For instance, cities like Huzhou and Guangzhou showed a HH clustering pattern, while the adjacent units tended to a LH clustering pattern. The reason may be that the urban green space system with high economic development levels is relatively complete, which can effectively balance the loss and alleviate the disturbance to ecosystem (Qiao, 2022). Most regions’ spatial autocorrelation distributions did not change distinctly. In addition, Liu (2018) found that there existed path dependence between provincial urbanization aggregation and ecosystem coordination, which also applied to the municipal scales of this paper. For example, Zhangjiakou, Hengshui, Cangzhou and other cities in Hebei Province behaved LH clustering patterns during the study period. Their spatial effects were not obvious and spatial relationship between EHI and UI was less coordinated compared with Beijing and Tianjin. Cities such as Nantong, Suqian, Taizhou and Lianyungang in Jiangsu Province exhibited similar characteristics as well.

4.3 Analysis of urbanization and ecosystem health drivers

UI and EHI were negatively correlated at the factor level (Fig 10), being consistent with others’ findings (Wu, 2021; Qiao, 2022). Coercive effect of urbanization on terrestrial ecosystem health mainly manifested in land degradation, environmental pollution and resource consumption. And terrestrial ecosystem health degradation would in turn hinder the development of urbanization (Chai, 2021). Nevertheless, their relationship are constantly changing. Wu (2021) demonstrated that the impact thresholds of different urbanization types on ecosystem health varied, and the direction of effects changed after reaching the threshold. In addition, there are differences in the effects of different urbanization development stages on terrestrial ecosystem health. For example, Chen (2022) concluded that there was a U-shaped relationship between EHI and UI. That is, EHI was negatively affected by the organic and neighboring urbanization process at the early stage of urbanization, while with the increasing investment in environmentally friendly and eco-friendly technology, the UI began to have an overall positive effect on EHI. Furthermore, Wu (2022) demonstrated that in the initial phase of urbanization in 2000, the population’s migration posed a threat to ecosystem health, as population, economy, and land all played interdependent roles in meeting the demands of urban living and production. However, during the transitional stage of urban development, the influence of economic urbanization on ecosystem health gradually diminished.
Urbanization process is driven by human factors (e.g., demography, economics, institutions and policies) and biophysical factors (e.g., topography and climate) (Alberti, 2010). Social and economic factors were the main driving force for urbanization development (Fig 11). Among them, GDP and population were the key factors stimulating urbanization (Zhang and Du, 2022). Economic development drove population migration such as rural people changing to urban peopole. The increase in population density was often accompanied by increased energy consumption, housing and transportation demand (Song, 2020). To meet the demand from a rapidly growing population, urban construction land expanded rapidly, and urban structure and functions tended to be complicated. Changes in land quantity and morphology directly affected vegetation cover and landscape connectivity, then influenced ecosystem capabilities to maintain their structure, function, and resist external disturbances (Peng, 2017). However, natural factors (i.e., climate and topography) had smaller path coefficients compared to social and economic factors, but played a critical role in ecosystem health variations (Fig 11). Studies have proved that responses to climate change varied among ecosystems, and terrestrial vegetation area has the capacity to mitigate climate change impacts (Li, 2018). Vegetation growth was more sensitive to the combined effects of water and heat (Mu, 2013). The increase in air temperature and precipitation could significantly improve the regional vegetation condition (Shen, 2019). Meanwhile, solar radiation affected vegetation cover mainly through plant photosynthesis. Additionally, elevation and slope had less effect on urbanization, mainly because regional development with high altitude and steep terrain tended to require more capital investment (Zhang and Du, 2022).
Both direct and indirect effects of factors influenced ecosystem health changes. UI was positive with EHI at the national scale (Fig 11), suggesting that urbanization would promote ecosystem health when developed to a certain stage. Economic development has promoted technological progress and industrial structure optimization, and social system reforms have enhanced people’s environmental awareness. Correspondingly, urbanization created positive externalities, scale economies, and public service provision, which weakened the adverse ecological impacts (Ulucak, 2020). UI behaved a positive effect on EHI at the regional level (expect for the southwest region), with significant performance in east and north (Table 8). After 2014, China entered a new-type urbanization planning and steady promotion period. And its development entered a new normal stage , which is economic slowdown and strategic adjustment of industrial structure (Yu, 2021). Meanwhile, the implementation of the main functional area planning acts as a constraint and control on spatial land expansion. Intensive land development and use conducted in limited natural habitats. And woodlands are less affected by encroachment, natural growth of which offsets the negative effects of urbanization (Wang, 2020). Since the late 1970s, China has implemented six key ecological restoration projects (e.g., the Three-North Shelter Forest Program, the Natural Forest Protection Project, the Grain for Green Program, the Returning Grazing Land to Grassland Project, etc.) to restore degraded ecosystems (Lu, 2018). These projects together cover 44.8% of forestlands and 23.2% of grasslands in Chinese terrestrial ecosystems (Lu, 2018), which have promoted vegetation coverage and ecosystem resilience to disturbance (Bryan, 2018). Regions such as east, central and northwest have benefited from these ecological protection policies to improve terrestrial ecosystem health. Social, economic and topography factors made indirectly positive effects on EHI via UI, but varied among regions (Table S10 and Table S12). Other studies also highlighted the positive indirect effects of human activities to woody vegetation growth (Tong, 2018). However, successful implementation of ecological restoration is closely related to the combined effects of climate conditions and human management (Tong, 2017). The southwest region has complex topography and uneven distribution of precipitation, combined with poor management practices (Tong, 2017). Ecological restoration in this area exhibits lower effects, making the negative impact of urbanization on ecosystem health still exist.

4.4 Comparison with previous studies

Since the concept of ecosystem health was introduced, scholars have tried to assess the health status of ecosystems by quantitative means. Among them, the VOR approach proposed by Costanza has been recognized and widely used in ecosystem health measurement at different scales. In recent years, ecosystem services have been identified crucial to human well-being, and they are included as one of the indicators in the ecosystem health measuring system. Thus, the VORS (vigor-organization-resilience-ecosystem service) framework further refines regional ecosystem health measurement. However, Hernández-Blanco (2022) pointed out that healthy ecosystems are linked to human social and economic development through the provision of ecosystem services, and the relationship between the two is complex. In view of the above controversies, this paper adopted a traditional VOR method to assess ecosystem health status. In addition, China has implemented localized policies for the growth of urbanization development and environmental protection, resulting in significant variations in spatial and temporal distributions of UI and EHI in various regions. Numerous studies on urbanization and ecosystem health have been conducted at the national scale (Wu, 2021; Chen, 2023; Liu, 2023). However, our study focuses on analyzing the relationship and driving effects at the national and regional scales, which are not often studied. Ultimately, we hope to propose insightful development recommendations for regional development and ecological conservation.
Population agglomeration and urban spatial expansion lead to a decline in ecosystem health by affecting energy consumption and vegetation green cover was supported by many studies (Liu, 2018; Zhang, 2022). However, the driving path coefficients of the comprehensive urbanization index and ecosystem health index in 2020 indicated that urbanization development showed positive ecological effects in most regions (Table 8), which is also proved by Yu’s study. Therefore, it is necessary to pay close attention to the relationship and driving effects of urban development and ecological conservation in different regions, so as to better grasp the coordinated evolution of both, and implement necessary anthropogenic regulation measures.

4.5 Limitations and uncurtains

There exist limitations to our study. First, the results were subject to data scarcity and potential errors in Statistical Yearbook data, in which adjacent years’ data was applied to supplement due to the absence. Second, the construction of UI and EHI measuring system is subjective. Different selected indicators will produce large differences in the final assessment results. NDVI was chosen as a surrogate for NPP to reflect vegetation vigor under the condition that the measurement with relatively coarse-classification schemes is involved, considering that the acquisition of NDVI data was much more convenient (Xu, 2012). Furthermore, our main purpose of this paper is to quantify and analyze changes and drivers on large spatial scales, so the selection of the two indices does not make much difference in the final results. Based on previous studies, the selection of indicators in this paper takes into account as many aspects reflecting UI and EHI as possible. On PLS-SEM, more valid samples are chosen to improve model accuracy, and driving factors’ interaction effects on latent variables should also be considered. In addition, the research time should be extended to analyze the driving mechanisms under different developmental stages, and we only chose 2020 in this article.
Nevertheless, it has research value and practical significance, which not only enriches the study of spatial patterns and temporal evolutions of UI and EHI of China in the past 20 years, but also provides a comparative and detailed analysis of their driving mechanisms.