Ecological Value Analysis Based
on Land Use Change in Liuhe
District of Nanjing, China (2009, 2019)
Wang, B.1 Liu, D. Y.2*
1. Nanjing Academy of Urban Planning & Design Co. Ltd, Nanjing
210005, China;
2. State Key Laboratory of Soil and Sustainable Agriculture,
Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
Abstract: The ecological value refers to
the valuation of ecosystem service function, which includes the value of market
functions (i.e., economic value) and the shadow value of non-market functions
(i.e., natural value). Given that different land-use patterns result in varied
service values, this study investigated recent urban and rural spatial changes
in the Liuhe district of Nanjing, China, over a 10-year period, especially
driven by the state-level new area strategy. Using Landsat TM data with a 30-m
resolution, spatial datasets of land use in 2009 and 2019 were obtained by
image interpretation. Costanza’s natural value estimation method was applied to
calculate the profits and losses of ecological value caused by land-use change.
From 2009 to 2019, the expansion of construction space (residential/service
land, industrial/mining land, and transportation/other land) led to a decrease
of 3.3% in the natural value of the whole district. According to the strong
sustainable development principle of “natural value cannot be reduced”, the
Liuhe district is deemed to be in a weak state of sustainable development.
Considering the ecological value of non-construction space (water area,
woodland, wetland, grassland, and cultivated land), the “uneconomical” phenomenon
was investigated under the logic of “economic civilization” in urban and rural
spatial expansion. The ratio of ecological value between non-construction and
construction spaces increased from 1: 5 to 1: 3, indicating that the comprehensive benefits of construction space are no
longer prominent. Accordingly, it is necessary to limit the occupation of
non-construction space such as water area by the extensive expansion of urban
and rural construction land.
Keywords: state-level
new area; land-use
change; ecological profit and loss; Liuhe district; Nanjing city
Data
Avialable Statement:
The dataset supporting this paper was
published and public available at: Wang, B., Liu, D. Y. Dataset of land use and
its ecological value assessment in Liuhe district of Nanjing city (2009, 2019)
[DB/OL/J]. Global Change Data Repository, 2020. DOI:10.3974/geodb.2020.05.17.V1.
1 Introduction
Through
its long period of industrial civilization, both the quality of the ecological
environment and the efficiency of resource utilization have declined in some
regions of China, rendering a disharmonious relationship between man and
nature. The prime reason for this situation is that most of the contribution
that eco-environmental system services make to human welfare is purely public
welfare, without directly increasing human welfare in the form of a monetary
economy. In many cases, people are not even aware of the existence of
eco-environmental system services[1–3].
It should be
recognized that the estimation of ecological value, especially the natural value,
is a problematic issue worldwide. Since the concept of ecosystem service
function was first proposed by the “Study of Critical Environmental Problems”in
1970[4–5], many ecologists, economists, and policy makers have
carried out a staggering mountain of research work. In 1997, Costanza et al. [1] published the
infamous article, “The value of the world’s ecosystem services and nature
capital” in Nature, which had great
repercussions felt globally. Costanza et
al.[1] divided the global
ecosystems into 16 categories, such as woodland, grassland, and cultivated
land, while their service functions were divided into 17 categories, such as
gas regulation, climate regulation, water regulation, and soil formation. Subsequently,
the value of global ecosystem service functions was estimated, showing that
that the average annual value of the global biosphere ‘industry’ was 33
trillion US dollars, equivalent to 1.8 times gross national product (GNP) of
the same period. Later, Zong et al.[6]
(2002) analyzed the value structure of regional ecosystem service functions in
Lingwu city of Ningxia, China, thereby extending Costanza et al.’s work from the simple estimation of natural value to the
comprehensive estimation of natural value and economic value. It was pointed
out that an increase or decrease in the natural value ought to serve as the
core index to measure whether a town or a region can realize sustainable development,
which in so doing must meet the requirements of the strong sustainable development
principle of “natural value cannot be reduced”[7–8].
In follow-up research—essentially following Costanza’s theoretical framework
but combining it with the actual situation in China—the ecological value
coefficient of various ecosystems has been revised[9–-11],
while the changes in ecological value caused by land-use changes have been
extensively explored[12–18].
On June 27, 2015,
the State Council officially approved the establishment
of Jiangbei new area in Nanjing city, Jiangsu province. Located north of the
Yangtze River, Jiangbei includes parts of Liuhe district and Pukou district, with
a planning area of 788 km2[19].
Meanwhile, Jiangbei and its surrounding rural areas are coordinated as a whole,
encompassing a total area of 2,451 km2 (Figure 1). Jiangbei is being
positioned not only as an independent innovation pilot area, a new urbanization
demonstration area, and a modern industrial agglomeration area in the Yangtze
River Delta, but also as a pivotal platform for the cooperation and opening up
of the Yangtze River Economic Belt (together referred to as “three zones and
one platform”). Liuhe district, as an integrated development area within the planning and coordination scopes of
Jiangbei, has always been the leading functional area of eco-tourism and agricultural
development in Nanjing. At least 80% of its territory is cultivated land, water
area, and woodland, and the proportion of these three land-use types in 2019
totaled 83.54%[22].In
recent years, the pace of urban construction has accelerated in Jiangbei under the guidance of the state-level new area
strategy. The subcentral city of Liuhe and the new town of Longpao have since
become urban areas with highly dense populations and developed economic and
industrial activity next to the central city of Jiangbei within the scope of
the new area, which has driven reductions in the availability of
non-construction land. Therefore, the establishment of ecological values and
their accounting, together with the coordination of ecological protection and
urban construction, are keys to achieving a high-quality development of Liuhe
district.

Figure 1 Location of Liuhe district and
state-level Jiangbei new area in Jiangsu province, China
|
Given that
different land-use patterns result in varied service values, this study investigated
the profits and losses of ecological value in the Liuhe district of Nanjing
over the past 10 years, especially driven by the state-level new area strategy.
Spatial datasets of land use were obtained via image interpretation based on
Landsat TM data. Ecological values of different ecosystems were comprehensively
assessed based on international natural value estimation methods[1–3]
combined with domestic comprehensive capital estimation methods. Considering
the ecological value of non-construction space (water area, woodland, wetland,
grassland, and cultivated land), the ratio of ecological value between
non-construction and construction spaces has increased over time from 1: 5 to
1: 3. Hence, we advise that further occupation by urban and rural construction
land of remaining non-construction space such as water area should be restricted.
2 Metadata of the
Dataset
The metadata of the dataset[22]
are listed in Table 1.
Table 1 Metadata summary of
the dataset
Items
|
Description
|
Dataset full name
|
Dataset of land use
and its ecological value assessment in Liuhe district of Nanjing city (2009,
2019)
|
Dataset short name
|
Land Use Ecological
Value Assessment in Liuhe
|
Authors
|
Wang, B.
AAZ-3013-2020, Nanjing Academy of Urban Planning & Design Co., Ltd,
279813263@qq.com
Liu, D. Y.
AAZ-2671-2020, State Key Laboratory of Soil and Sustainable Agriculture,
Institute of Soil Science, Chinese Academy of Sciences, dyliu@issas.ac.cn
|
Geographical region
|
Liuhe district of
Nanjing city, Jiangsu province, China
|
Data age
|
2009, 2019 Time resolution 10 years
|
Spatial resolution
|
30 m Data
format .adf, .xlsx
|
Data size
|
2.47 MB (940 KB after
compression) Data files 36 documents
|
Foundation
|
National Natural
Science Foundation of China (41977049)
|
Computing environment
|
ArcGIS
|
Data publisher
|
Global Change
Research Data Publishing & Repository, http://www.geodoi.ac.cn
|
Address
|
No. 11A Datun Road,
Chaoyang District, Beijing 100101, China
|
Data sharing policy
|
Data from the Global
Change Research Data Publishing & Repository includes metadata, datasets
(data products), and publications (in this case, in the Journal of Global
Change Data & Discovery). Data sharing policy includes:
(1) Data are openly available and can be freely downloaded via
the Internet; (2) End users are encouraged to use Data, subject
to citation; (3) Users, who are by definition also value-added service
providers, are welcome to redistribute Data, subject
to written permission from the GCdataPR Editorial Office and the issuance of
a Data redistribution license, and; (4) If Data are
used to compile new datasets, the ‘ten percent principal’ should be followed,
such that Data records utilized should not surpass 10% of the
new dataset contents, while sources should be noted in suitable places in the
new dataset[23]
|
Communication and searchable system
|
DOI, DCI, CSCD,
WDS/ISC, GEOSS, China GEOSS, Crossref
|
3 Research Area and Data Development
Methods
3.1 Research Area
Liuhe district has distinct
natural resources and cultural characteristics. Situated between the Yangtze
River and Chuhe River, its northern hills are undulating. Going from north,
natural mountains and rivers give way to a geological
garden area and subcentral city in the middle, with a wetland polder area and
new town in the south. Its northern part is one of the two garden areas in
Nanjing, constituting both an ecological protection and suburban urban-rural
integration development area. In the central and southern area, the part west
of the ring expressway is a highly urbanized metropolitan area built within a
40-km radius of Xinjiekou, while the part east of the ring expressway is home
to a riverside ecological protection and suburban urban-rural integration
development area (Figure 2). The new version of the master plan puts forward
the overall pattern of “northern-southern gardens, central metropolis,
riverside development, and urban-rural integration”[20].
The Chuhe River basin, wherein Liuhe district is located, has been an vital place for human settlement in prehistoric and ancient
times. Liuhe is also the main producing area of Yuhua stone, which is a
national treasure given by nature and uniquely found in China. It is also the
birthplace of the Jiangsu folk song ‘Jasmine’.
3.2 Data Development Methods

Figure 2 Spatial structure planning of
Nanjing[20]
|
3.2.1
Land-use Quantity and Its Distributional Changes
(1)
Analyzing land-use quantity and its distributional changes
The quantity of
land resources available determines its degree of scarcity. First, their
changes in quantity can be gauged by the total areas of different land-use
types. Through analyzing the total change undergone for one or more land-use
types, we can grasp the general trend of land-use changes over time and space.
Second, such changes could be conveyed also in terms of per capita change of
differing land-use types, which can more directly reflect quantitative changes
in land use.
According to the
“Classification of land use status”[24] and considering the characteristics
of Liuhe district, we divided the land-use types providing ecosystem service
functions into eight categories: cultivated land, woodland, wetland, grassland,
water area, residential/ service land, industrial/ mining land, and
transportation/other land. Based on Landsat TM images from 2009 and 2019, the
data on land-use change in Liuhe district over a 10-year period were obtained,
by using ArcGIS v10.5 (ArcGIS, ESRI Inc., Redlands, CA, USA) to calibrate coordinates,
cut grids, and identify the pertinent attribute data. To compare the changes in
the spatial distribution of land use, both the statistical yearbook of Liuhe district[25] and Nanjing’s annual
report of urban planning [26]were queried to extract supervision
data of land-use classification and other comparative reference data.
(2) Analyzing
changes in land-use structure
Given the tight
correlation between economic structure, land-use structure, and ecosystem
service function, investigating the structure-function relationship can better
fulfill the role of land use as a macroeconomic means.
The land-use dynamic index (LUDI) expresses the change in the area of a
certain land-use type per
unit time; that is, the change rate of this given land-use type in area. It is
calculated this way:
(1)
where Ua and Ub
represent the area (km2) of a certain land-use type at time a and b, respectively, and T is
the length of the study period, from time a
to time b. When T is in years, LUDI represents the annual change rate of this
land-use type in area.
3.2.2 Ecosystem
Service Classification System
Here,
the value of regional ecosystem service functions was divided into two
components (natural value and economic value) with a total of 24 items based on
the theoretical framework of Costanza et
al. [1] and informed by localized estimation experience of Zong et al. [6], coupled to the
actual situation in Liuhe district. The natural value comprised 12 items, gas
regulation, climate regulation, interference regulation, water regulation,
water supply, erosion prevention, soil formation and nutrient cycling,
environmental protection, waste treatment, pollination, biological pest
control, and habitat (shelter). The economic value also comprised 12 items,
agricultural value, forestry value, animal husbandry value, aquatic product
value, industrial value, construction industry value, transportation and
storage value, wholesale and retail value, accommodation and catering value,
financial industry value, real estate industry value, and tourism and other
service industry value.
3.2.3 Ecological
Value Estimation Methods
According
to the current statistical caliber, this study considered the economic value
while paying special attention to the natural value of ecosystem service
functions. To do this, important non-market regulation and purification
functions plus habitat and life support functions were taken into account by a
specific estimation method, for which “the natural value cannot be reduced” is
the principle of strong sustainable development of urban and rural areas[7–8]. Based on land-use data and
ecological value accounting theory, the ecological value per unit area (Yuan·hm‒2·a‒1)
was estimated; then, the ecological value was calculated for 2009 and 2019
based on the total areas of various ecosystem types present in the region in
each year[1–3].
(1)
Estimating natural value
Natural value is
mainly provided by cultivated land, woodland, wetland, grassland, and water
area. The natural value coefficient of 12 ecological service functions[1–3]
was used to derive the natural value of ecosystem service function per unit
area, after corrections. To ensure the consistency between natural value and
economic value estimations, 1997 was taken as the benchmark year. The 1997–2019
data were obtained from the “Nanjing Statistical Yearbook” [27] to
calculate the consumer price index of Nanjing in 2019, which was
144.2 (it was 100 in 1997). Based on this, the global universal value
coefficient of Costanza et al. in
1997 could then be converted into the value coefficient of Nanjing region in
2019.
(2)
Estimating economic-social value
Economic value
mainly refers to the economic production function of ecosystems, that is, those
marketized products or utility as provided by different ecosystems. Traditional
statistical methods mainly infer economic value from GNP. To avoid repeated
calculations, this study classified the economic value of a give ecosystem
according to its corresponding land-use type. In this way, agricultural value
belonged to cultivated land, and likewise forestry value to woodland, animal
husbandry value to grassland and cultivated land, aquatic product value to
water area and wetland, industrial value and part of construction industry value
to industrial and mining land, and transportation and storage value to
transportation and other land. Similarly, for the values of wholesale and
retail industry, accommodation and catering industry, financial industry, real
estate industry, tourism and other service industries, and part of the value of
construction industry, they all belonged to residential and service land. The
economic-social value of ecosystem service function per unit area (10 thousand
Yuan·hm‒2·a‒1) was then calculated as follows:
(2)
where Vi is the economic-social
value per unit area of industry i (10
thousand Yuan·hm‒2·A‒1), Gi is the gross domestic product (GDP: 10 thousand
Yuan), and Si is the area
of industry i (hm2).
4 Results and
Validation
4.1 Dataset Products
The
dataset includes spatial data and table data. The spatial data include land use
data in 2009 and 2019. The spatial resolution is 30 m. The table data include:
(1) area and proportion of different land-use types in 2009 and 2019; (2) LUDI
from 2009 and 2019; (3) natural value of ecosystem service functions per unit
area in 2019; (4) economic value of ecosystem service functions per unit area
in 2019; (5) ecological value of different ecosystem types in 2009 and 2019.
The dataset is archived in ArcGIS Grid (.adf) and .xlsx data format, which
consists of 36 data files with data size of 2.47 MB (compressed to 931 KB in
one file).
4.2 Data Results
4.2.1 Spatial Changes
of Land Use in Liuhe district
(1)
Quantitative changes of land use

Figure 3 Changes of
land-use area in Liuhe district of Nanjing from 2009 to 2019
|
From 2009 to
2019, the residential/service land,
industrial/mining land, transportation/other land, woodland, and
grassland all increased in total area, while the water area, wetland, and
cultivated land each decreased (Figure 3). The per capita land area* decreased from 0.21 hm2 in
2009 to 0.18 hm2. In particular, the cultivated land area for human
survival has been reduced by 20%, from 0.10 hm2 to 0.08 hm2,
while the per capita residential/service land remained stable, at 0.018 hm2.
Therefore, it will soon approach the 0.053 hm2 warning threshold of
the Food and Agriculture Organization of the United Nations that would threaten
the food supply capacity.
(2)
Distributional changes of land use
After conducting
the spatial overlap analysis, it was evident that the expansion of urban
construction space was mainly concentrated in the subcentral city Liuhe. The
expansion of living space and spread of economic development zone go together.
Influenced by ecological restoration strategy, the woodland and grassland
increased in the northern and central-northern areas (Figure 4–6).
(3)
Structural change of land use
From 2009 to
2019, the cultivated land showed the largest range of change, followed by that
of water area. The proportion of these two land-use types out of total land use
declined from 67.33% in 2009 to 65.12%, with an absolute decrease of 2.21
percentage points. Corresponding to that decrease, the residential/service
land, industrial/ mining land, and transportation/other land together increased
by 1.76% over the past decade (Figure 7).
According to the LUDI of various land-use
types, the annual change rates of industrial/mining land (–0.026) and wetland
(0.02) spanning the 10 years were the greatest, followed by grassland (–0.018), residential/service land (–0.011), transportation/other
land

Figure 4 Land use
status of Liuhe district in 2009
|
Figure 5 Land
use status of Liuhe District in
2019
|
Figure 6 Spatial changes of Liuhe
district construction from 2009 to 2019
|

Figure 7 Changes of land-use structure in Liuhe district of Nanjing from 2009 to 2019
|
(–0.009),
and least for water area (0.004), woodland (–0.003), and cultivated land (0.003).
The primary reason for the pronounced annual change rate of industrial/mineral
land is that the manufacturing industry- bearing function has been strengthened.
There are three major reasons for the moderate increases found in residential/service
land, and transportation/other land. First, the central urban area of Nanjing
has formed a closed loop of coordinated development, which is beneficial for
Liuhe to undertake the functional spillover. Second,the construction of Liuhe subcentral
city as an “anti-magnetic” center has sped up. Third, the Jinniuhu plate has
achieved a qualitative leap. In contrast, the growth of woodland and grassland
is mainly due to the restoration of northern garden areas in Nanjing.
4.2.2 Ecological
Value Profits and Losses in Liuhe district
(1)
Natural value and economic value
The natural
value of ecosystem service function per unit area is presented in Table 2. Evidently,
the total natural value of wetland was the highest. Considering the economic value
of ecosystem service function per unit area, that of industrial/mining land was
the largest; the economic values of wetland, water area, and woodland were all
relatively low (Table 3).
Table 2 Natural value of ecosystem service function per unit area in Liuhe district of
Nanjing in 2019 (10 thousand Yuan·hm‒2·a‒1)
Ecosystem types
|
Gas regulation
|
Climate regulation
|
Disturbance regulation
|
Water regulation
|
Water supply
|
Erosion control
|
Soil formation
|
Nutrient cycling
|
Waste treatment
|
Pollination
|
Biological control
|
Habitat/shelter
|
Total value
|
Woodland
|
–
|
0.17
|
0.003
|
0.003
|
0.004
|
0.12
|
0.013
|
0.44
|
0.12
|
–
|
0.003
|
0.28
|
1.156
|
Grassland
|
0.01
|
–
|
–
|
0.004
|
–
|
0.05
|
0.001
|
–
|
0.12
|
0.03
|
0.03
|
0.26
|
0.505
|
Wetland
|
0.16
|
–
|
5.44
|
0.03
|
4.56
|
–
|
–
|
–
|
5.01
|
–
|
–
|
0.38
|
15.58
|
Water area
|
–
|
–
|
–
|
6.52
|
2.54
|
–
|
–
|
–
|
0.81
|
–
|
–
|
0.26
|
10.13
|
Cultivated land
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
0.02
|
0.03
|
–
|
0.05
|
Notes: ① Data were derived from Costanza et al.[1–3]. In 1997, the official exchange rate of US
dollar to the RMB was 1: 8.3. ②
Costanza et al. did
not assign value to the function of habitat (shelter) when calculating the
ecological value of woodland, grassland, or water area. Here, the mean value of
wetland and estuary was used to revise the natural value coefficient of habitat
(shelter) of woodland, grassland, and water area. ③ In 2000, the average per unit area values[9]
of woodland and cultivated land were 18,789 and 13,054 Yuan·hm–2,
respectively; the consumer price index of Nanjing was
98.6 (100 in 1997), whose conversion into per unit area values of woodland and
cultivated land in 1997 were 19,056 and 13,240 Yuan·hm–2. In 2019,
the per unit area values of woodland and cultivated land were 27,479 and 19,093
Yuan·hm–2. When calculating the ecological service value later, the
revised data shall be used.
Table 3 Economic value of ecosystem service
function per unit area in Liuhe district of Nanjing in 2019 (10 thousand
Yuan·hm‒2·a‒1)
Ecosystem types
|
Cultivated land
|
Woodland
|
Wetland
|
Grassland
|
Water area
|
Residential/ service land
|
Industrial/
mining land
|
Transportation/ other land
|
Economic value
|
8.25
|
1.92
|
4.28
|
6.5
|
4.28
|
199.13
|
559.44
|
6.05
|
(2) Profits and losses of ecological value
The ecological values of different ecosystem types (Table 4) were obtained
based on the ecological value per unit area of each ecosystem type, combined
with the total area. By analyzing the results of ecological value accounting,
the profits and losses of ecological value from 2009 to 2019 were derived.
Table 4 Ecological values of different ecosystems in Liuhe district of Nanjing (100 million
Yuan·a‒1)
Ecosystem types Year
|
Cultivated land
|
Wood
land
|
Wetland
|
Grassland
|
Water area
|
Residential /service land
|
Industrial/mining land
|
Transportation/other land
|
Total value
|
Ecological value
|
2009
|
62.29
|
9.81
|
2.17
|
0.89
|
37.35
|
226.59
|
120.22
|
3.29
|
462.61
|
2019
|
60.32
|
10.07
|
1.73
|
1.06
|
36.03
|
250.74
|
151.78
|
3.59
|
515.32
|
Natural value
|
2009
|
11.71
|
5.78
|
1.70
|
0.06
|
26.26
|
—
|
—
|
—
|
45.51
|
2019
|
11.34
|
5.93
|
1.36
|
0.08
|
25.33
|
—
|
—
|
—
|
44.04
|
Economic value
|
2009
|
50.58
|
4.03
|
0.47
|
0.83
|
11.09
|
226.59
|
120.22
|
3.29
|
417.10
|
2019
|
48.98
|
4.14
|
0.37
|
0.98
|
10.70
|
250.74
|
151.78
|
3.59
|
471.28
|
(i) The total
natural value of various ecosystems decreased from 4.551 billion Yuan in 2009
to 4.404 billion Yuan in 2019, with a decrease of 147 million Yuan. The
increasing occupation of surrounding cultivated land, water area, and wetland
by urban and rural construction land, continuously drove down the natural value
of these three ecosystems on yearly basis. In contrast, thanks to the increase
in woodland area, its natural value rose from 578 million to 593 million Yuan.
However, the natural value still decreased by 3.3%. According to the principle
of “natural value cannot be reduced”, it's in a weak sustainable development
state. Therefore, to ensure the extant area of woodland is not reduced, the occupation
of the surrounding cultivated land and water area by urban and rural
construction land should be mitigated as far as possible.
(ii) The total
economic value of various ecosystems increased from 41.710 billion Yuan in 2009
to 47.128 billion Yuan in 2019, amounting to a net increase of 5.418 billion
Yuan. This increase mainly arose from increased urban and rural construction
land areas. The economic value of residential/service land increased from
22.659 billion to 25.074 billion Yuan, as did the economic value of industrial/mining
land (from 12.022 billion to 15.178 billion Yuan). The economic values of
cultivated land, water area, and wetland all gradually fell due to considerable
displacement of these ecosystems by urban and rural construction land.
(iii) The total
ecological value of various ecosystems increased from 46.261 billion Yuan in
2009 to 51.532 billion Yuan in 2019, representing a net increase of 5.271
billion Yuan. Of this, natural value and economic value accounted for 9.84% and
90.16% (in 2009) and 8.55% and 91.45% (in 2019), respectively. The proportion
of natural value has continuously shrunk, a trend
which suggests that the expansion of urban and rural construction land is
unavoidably accompanied by the loss of natural value (e.g., cultivated land and
water area).
(iv)
In 2009, the total natural value of various
ecosystems (4.551 billion Yuan) accounted for 10.91% of their total economic
value (41.710 billion Yuan). In 2019, the total natural value (4.404 billion
Yuan) accounted for 9.34% of their total economic value (47.128 billion Yuan).
In the past decade, the ratio of natural value to economic value has decreased
from one-ninth to one-tenth, demonstrating that the expansion of urban and
rural construction land has impaired the service function of ecosystems.
Therefore, in the process of economic accounting, we should not only consider
the growth of economic value, but also the parallel loss of natural value, so
as to reflect the rate of economic growth more truthfully.
(v) Considering
different types of ecosystems, non-construction space (water area, woodland,
wetland, cultivated land, and grassland) plays vital role in sustaining life
support systems. The natural value of wetland per unit area is the largest,
followed by water area, woodland, cultivated land, and grassland. Still, when
considering economic values, those of construction space (residential/service
land, industrial/mining land, and transportation/other land) are dozens of
times greater than those of woodland and water area. Therefore, in the
development of urban and rural construction land, the potential value of
woodland and water area is overlooked, resulting in a loss of natural value.
When comprehensively assessing the relationship between the economic value and natural
value of each ecosystem, the economic value of non-construction space in 2009
accounted for 19.1% of the economic value of construction space; this ratio
fell to 16.1% in 2019. However, considering both the
natural value and economic value, the ecological value of non-construction
space accounted for 32.2% of the ecological value of construction space in
2009, but less so (26.9%) in 2019. Therefore, concerning the non-market valuation of ecosystems, the ratio of
ecological value between non-construction and construction spaces has risen
from 1: 5 to 1: 3. Hence, the comprehensive benefits of urban and rural
construction land are no longer prominent. Accordingly, it is necessary to
limit the occupation of non-construction space including cultivated land, woodland,
and water area by further extensive expansion of urban and rural construction
land.
4.3 Date Validation
Taking
Lingwu of Ningxia as an example, Zong et al. (2002) [6] extended the
simple estimation of natural value by Costanza et al. [1] and
derived a comprehensive estimation of natural value and economic value. Here,
we verified our results by comparing them with the data from Lingwu. From 1990
to 1997, due to industrial development in Lingwu, especially five types of
small enterprises (including chemistry and metallurgy),
the loss of natural value became increasingly prominent, with an annual
decrease of 4% on average. In terms of the ecological value, its rate of
increase lagged behind that of GDP in Lingwu. From 2009 to 2019, driven principally
by the state-level new area strategy, the city-industry integration of Liuhe
subcentral city accelerated, resulting in a concomitant greater loss of natural
value marked by an average annual decrease of 3.4%. The growth rate of
ecological value was also lower than that of GDP. It should be pointed out that
because of different regions and time periods, especially the distinct stages
of regional urbanization, the comprehensive estimation of ecological value is
partially influenced by the estimation of economic-social value; hence, certain
differences are perhaps inevitable between the present and previous studies.
Considering
that differing land-use patterns result in varied service values, this study explored
the urban and rural spatial changes in Liuhe district in the last 10 years,
especially driven by the state-level new area strategy. The profits and losses
of ecological value caused by land-use changes were analyzed by refining the
service functions as far as possible based on Costanza’s and other value
accounting methods. The findings could provide timely support for measuring
regional sustainable development.
The results
indicate that the expansion of construction space has led to 3.3% reduction in
the natural value, rendering the whole district in a weak sustainable development state. Considering the ecological
value of non-construction space, this study analyzed the “uneconomical”
phenomenon under the logic of “economic civilization” in urban and rural spatial
expansion. As the ratio of ecological value between non-construction space
(represented by five ecosystems) and construction space (represented by three
ecosystems) has increased from 1:5 (simple estimation of economic value) to
1:3, the comprehensive benefits of construction space are no longer prominent
in the study area.
The accounting of
ecological value for each type of ecosystem includes both natural value and
economic value. Specifically, the natural value is the potential value of the
ecosystem, which cannot be marketized. Through our estimations, we find that
under the influence of traditional values, economic indicators are rather
incomplete. If economic indicators are solely relied upon for decision-making,
it would lead to a waste of resources and the destruction of ecological environment.
Further, the
significance of this study lies in reviewing the “economic civilization” logic
of urban and rural spatial expansion,and unveiling the “uneconomical” aspects hidden within “economic
civilization”. Under a revamped logic centered on “ecological civilization” in
the new era, land space development that maximizes ecological value while maximizing
comprehensive benefits should be carried out in a carefully planned,
step-by-step manner.
Due to the
diversity and complexity of ecosystem service functions, it is challenging to
achieve comprehensive and accurate assessments of ecological value.
Nevertheless, it is a laudable and correct
process to estimate the minimum value of ecological service function by referring
to leading research practices in China and elsewhere. This study, however, did not
consider the disastrous losses caused by
emergencies in natural, economic, and social processes, nor the impacts
of various bottlenecks, threshold effects, and abrupt events on valuations.
Author Contributions
Wang, B.
developed the frame of the dataset. Wang, B. and Liu, D. Y. designed dataset
processing. Wang, B. designed the models and algorithm. Liu, D. Y. performed
the data verification. Wang, B. wrote the data paper.
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