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.