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Journal of Resources and Ecology >

2019 , Vol. 10 >Issue 3: 282 - 288

DOI: https://doi.org/10.5814/j.issn.1674-764X.2019.03.006

Resource Econmy

Temporal and Spatial Variations of Eco-asset Patterns and the Factors Driving Change in the Wanjiang Demonstration Area

  • CAO Yuhong , * ,
  • CHEN Chen ,
  • LIU Chonggang ,
  • LI Lulu ,
  • LIU Meiyun
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  • College of Environmental Science and Engineering, Anhui Normal University, Wuhu, Anhui 241003, China
*Corresponding author: CAO Yuhong, E-mail:

Received date: 2018-01-22

  Accepted date: 2018-11-20

  Online published: 2019-05-30

Supported by

National Natural Science Foundation of China (41571124)

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Abstract

With the rapid development of the society and the economy, people are paying more attention to the value of natural resources and the benefits of the ecological environment. Evaluating the value of eco-assets has become a focus of concern. Quantitative remote sensing measurements, land data and other auxiliary data were used to measure the eco-assets in 46 regions of the Wanjiang Demonstration Area from 1990 to 2013. This paper analyzes temporal and spatial variations of eco-assets’ distribution, composition, change patterns and the factors driving variations. The results show that the distribution of eco-assets in the regions is very uneven, the central region has higher ecological assets than other regions, and it declined first and then rose during the period 1990-2013. The total amount of eco-assets increased by 3.05%. The change in the amount of ecological assets was not large, but it is important that the amount of assets was basically stable, and increases in the proportion of degraded areas was small. Grassland and water body eco-assets decreased by 11.19% and 0.66%, respectively, and that of cultivated land decreased by 15.54%, but forest land increased by 6.42%. As for the change pattern of ecological assets, the per capita assets of Hefei had the largest reduction, and those of Xuancheng the second largest. The spatial and temporal changes of ecological assets in the Wanjiang Demonstration Area include natural factors and human factors. The government's macro-control and economic policies are the main driving factors for the spatial and temporal changes of the ecological assets pattern.

Key words： eco-assets; landscape pattern; temporal and spatial variation; driving force analysis

Cite this article

CAO Yuhong , CHEN Chen , LIU Chonggang , LI Lulu , LIU Meiyun . Temporal and Spatial Variations of Eco-asset Patterns and the Factors Driving Change in the Wanjiang Demonstration Area[J]. Journal of Resources and Ecology, 2019 , 10(3) : 282 -288 . DOI: 10.5814/j.issn.1674-764X.2019.03.006

1 Introduction

Ecosystems not only provide humanity with abundant physical resources such as food, medicine and various raw materials, but also provide humankind with intangible non-physical ecological services such as climate regulation, soil and water conservation and so on, all of which are of enormous economic value. The concept of eco-assets has developed based on two other concepts, those of natural assets and ecosystem services; the concept of eco-assets combines and unifies these other concepts. Hu Yi argued that ecological resources need to meet three conditions: scarcity, value added and clearly established ownership. In recent years, global environmental problems have become more and more serious as resources have been depleted and population has grown. Eco-assets, which are based on the value of natural resources and ecological services, have attracted the attention of scholars in China and elsewhere, and become a hot research topic in the current ecological economy (Stewart and Vogt, 1997). The study of eco-assets in China began with environmental resource value assessments in the 1980s. At present, in foreign countries, research on the concept of ecological asset value has moved on to the construction of models, parameter correction and research on specific regional eco-assets. With the development of 3S technology, some scholars have applied macro remote sensing technology and geographic information technology to this research (Patterson et al., 2008). Liu et al. (2013) used quantitative remote sensing measurements to analyze the changes to eco-assets in the Yangtze River Delta and the forces driving change. The value of ecosystem service is for ecological protection, ecological function zoning, natural asset accounting. Moreover, the ecosystem service function presents spatiotemporal dynamic characteristics that are closely related to ecological structure and ecological function. However, a unified and complete dynamic evaluation method for ecosystem service value is lacking in China. Based on considerable research, Xie et al. (2015) improved the ecosystem service value method based on the unit area value equivalent factor, and this has promoted development of a domestic ecological asset appraisal method. With the development of eco-assets, the evaluation methods for eco-assets have become more and more varied. Fan et al. (2009) proposed a dynamic assessment index system for eco-assets with eco-asset consumption loss and transfer as content, and established a dynamic evaluation index and measurement model for eco- assets. The most fundamental reason for evaluating eco- assets is to protect ecosystems. Li et al. (2014) analyzed the economics of forest eco-asset operations in the state-owned forests from the perspective of value. Chen (2015) used grey correlation analysis and a regression tree to analyze seven factors potentially influencing the change of eco-assets in the upstream area of Ganjin. Derek et al. (2014) proposed a method for quantifying cultural services by collecting landscape preference data for individual landscape features and the structure and composition of whole landscapes to calculate the value of ecological asset services. Liu et al. (2014) used a dynamic energy-based urban model to accurately simulate resource consumption, economic growth and environmental impact in Beijing from 1999 to 2039. Erik (2015) used an in-depth survey of donors to explore the value of ecosystem services and discuss the impact of different feedback flows; he proposed a possible model and two possible major approaches. Adam (2014) used a capital assets framework to assess PES planned social, environmental, economic and institutional outcomes, focusing on efficiency, effectiveness and fair balance. They found that the ecosystem services program could provide positive protection and development outcomes for livelihoods, changes to land use, family and community incomes and governance. Suich et al. (2015) presented empirical evidence and the results of a review of knowledge states for mechanisms linking ecosystem services and poverty alleviation. And they reviewed the results to determine the status of current knowledge of the size and nature of these contacts and to focus on future research agendas. Ian (2011) took into account the flow of ecosystem services and their contributions to welfare payment products and, through a case study of land use changes, examined and interpreted the methods for assessing the benefits of the assessment. Bai et al. (2016) analyzed eco-assets and a hydrological time series, and used an InVEST model to study the impact of land management on ecosystem services. Barbier (2013) developed a way to incorporate ecosystem services into an asset appraisal framework. A number of deficiencies can be found in the studies of eco-assets by scholars from China and elsewhere: first, the research content focuses on the analysis of the structural characteristics of the time and space evolution of eco-assets; second, research focuses on ecosystem types such as forest, grassland and wetland, but there is a lack of research of the ecosystems of urban agglomerations; and third, studies are focused on particular regions like the San Jiang Yuan and Yangtze River Delta, while research on areas in central China is lacking.
Based on the above discussion, this paper has chosen the Wanjiang Demonstration Area as the research area to conduct a study of a region in central China. The study not only examines the types of land use, it also evaluates the eco- assets of a complex urban agglomeration ecosystem, and analyzes the time and space changes of eco-assets in the complex ecosystem. The study can serve as a reference for efforts to protect the ecological environment and to use land sustainably in the Wanjiang Demonstration Area.

2 Research method

2.1 Introduction to the research area

Wanjiang Demonstration Area is a growing economic region with a very important strategic position in central China. A total of 46 counties (cities and districts), including Hefei, Wuhu, Ma'anshan, Tongling, Anqing, Chizhou, Chuzhou, Xuancheng and Lu'an, form the Wanjiang Demonstration Area for carrying industrial transfer along the Yangtze River in Anhui province. The area has about 76000 km2 of land, accounting for 54% of the land area in Anhui, a population of 30.58 million, and gross domestic product reaching 581.8 billion Yuan (Zhao et al., 2011). The topography is complex and diverse with considerable differences between north and south; there is hilly terrain located between the Huaihe plain and the plains along the Yangtze River. There are hilly mountains in the west and south of the study area, and there are three well-known rivers distributed between the mountains. Cultivated land is the main land use type accounting for about 52% of the area, followed by forest land accounting for 33.3% of the area, and construction land accounting for about 6.3%.

2.2 Data sources and processing of data

Remote sensing data comes from the National Earth System Science Data Sharing Infrastructure (http://www.geodata.cn/). We downloaded TM images with less than 20% cloud cover in June 1990, June 2000 and June 2013, and with a spatial resolution of 30 m×30 m. After we used ENVI software to perform radiometric calibration, radiometric correction, atmospheric correction and geometric correction on remote sensing image data, the Wanjiang Demonstration Area was divided into 6 kinds of ecological systems by means of human-computer interaction, visual interpretation and supervision classification: forest land, grassland, cultivated land, water area (including rivers and lakes and wetlands), construction land (including land used for transportation and for industry and mining) and unused land. ArcGIS software was used to analyze the area of various types of meteorological data from the Anhui provincial meteorological observatory, including monthly average rainfall and monthly average temperature. Population and GDP data are taken from the statistical yearbooks for Anhui province.

2.3 Estimation of eco-assets

The concept of ecological assets is an open space-time dynamic concept. It refers to the sum of all service function values and natural resource values which are provided by various ecosystems within a certain time and space. Ecological assets vary with the type, area and quality of ecosystems in a region (Han et al., 2001). This paper makes reference to the value equivalence formula of spatiotemporal dynamics for ecological services (Xie et al., 2015), and then establishes the model to estimate eco-assets:
$V=\sum\limits_{n=1}^{m}{{{F}_{ni}}}\times {{S}_{n}}$ (1)
In this formula, V represents the value of eco-assets, Fni represents the value-equivalent factor per unit area in the ith eco-services of the nth ecosystem, and Sn represents the landscape patch area size of the nth ecosystem.

3 Analysis of the spatial patterns and driving forces of eco-assets

3.1 Spatial patterns of ecological assets

3.1.1 The spatial distribution of eco-assets in the Wanjiang Demonstration Area
Fig. 1 shows that Taihu County and Wuhu City had high eco-asset values in 1990, while Hanshan County, Anqing City, Tianchang City and Ma'anshan City had low values in that year. In 2000 Taihu County had high eco-asset values,and Xuancheng, Tianchang, Nanling and Ma'anshan had low values. In 2013, Taihu County, Dongzhi County and Qingyang County had high eco-asset values, while Fengyang County, Quanjiao County, Hefei, Susong, Nanling County and Xuancheng urban areas had low eco-asset values. From 1990 to 2013, there was no change in the maximum value of ecological assets. The value of ecological assets decreased year by year in Taihu County and Wuhu City, while the counties in East and Qingyang County increased year by year.
Table 1 Value-equivalent factors per unit area of the eco-system in Wanjiang Demonstration Area (Yuan)
Category Forest land Grassland Cultivated land Water area
Gas conditioning 3097.0 707.9 442.4 0
Climate regulation 2389.1 796.4 787.5 407.0
Water conservation 2831.5 707.9 530.9 18033.2
Soil formation and protection 3450.9 1725.5 1291.9 8.8
Waste disposal 1159.2 1159.2 1451.2 16086.6
Biodiversity conservation 2884.6 964.5 628.2 2203.3
Food production 88.5 265.5 884.9 88.5
Raw material 2300.6 44.2 88.5 8.8
Entertainment culture 1132.6 35.4 8.8 3840.2
Fig. 1 The spatial distribution of eco-assets in the study area from 1990 to 2013 (Yuan)
Based on the range of eco-assets in Anhui province from 1990 to 2013, Wanjiang Demonstration Area can be divided into seven grades: seriously degraded (less than 50%), moderately degraded (-50%-15%), lightly degraded (-15%-5%), basically stable (-5%-5%), mild growth (5%-15%), moderate growth (15%-50%) and rapid growth (more than 50%). The following conclusions can be drawn from Fig. 1 and Fig. 2. The area with high eco-assets is distributed mainly in the south of the Anhui demonstration area and includes Anqing City, Chizhou City and other areas. The area with degraded eco-assets includes Hefei City, Xuancheng City and other areas where there is rapid economic development. However, other county seats like Susong, Wangjiang and Taihu are regions that previously had large eco-assets, but due to economic development, the degradation of these eco-assets is also very serious.
Fig. 2 Temporal and spatial variation of eco-assets in the study area from 1990 to 2013
Fig. 2 shows the areas of Wanjiang Demonstration Area with the most seriously degraded ecological assets during the years 1990 to 2000 were in Susong County, Hefei City, Fengyang County and Xuancheng City. There were mildly degraded areas in Chizhou, Shitai County, Wuwei County and Dangtu County. The areas with seriously degraded ecological assets during the years 2000 to 2013 were located in the urban areas of Susong County, Hefei, Fengyang and Xuancheng, while the moderately degraded areas were located in Lu'an, Lujiang, Tongcheng, Wangjiang. The areas with mild degradation were distributed in Quanjiao County, Jingxian County and Jingde County, and the areas with relatively fast growth were located in Dongzhi County, Taihu County, Hanshan County and Qingyang County, ecological assets with a larger proportion of areas with moderate growth accounting for to 75% of the total area, and seriously degraded areas accounting for a small proportion of less than 10%.
3.1.2 Time distribution pattern of eco-assets
Tab. 2 shows that the eco-assets of Wanjiang Demonstration Area are mainly forest land and water areas. The value of forest land assets was 471640 million yuan in 1990 and the value of water assets was 264940 million yuan. The value of forest assets had increased to 501900 million yuan and that of water assets had decreased to 263190 million yuan by the year 2013 because the area is mainly forest land and water areas.
Table 2 The eco-asset classifications of the study area (100 million yuan)
Time\Main landscape types Forest land Grassland Cultivated land Water area Total
1990 471.64 4.11 29.34 264.94 770.03
2000 432.88 3.86 30.03 238.78 705.55
2013 501.90 3.65 24.78 263.19 793.52
Change rate (%) 6.42 -11.19 -15.54 -0.66 3.05
Cultivated land was found to be mainly degraded and from 1990 to 2013 decreased by 15.54%. The grassland decreased by 11.19% during the same years. These modest losses should get our attention. Forest land eco-assets grew by 6.42% and the total rate of growth was 3.05%. The areas of grassland and water areas were reduced due to climate change, population growth, urban development, and transportation and construction growth. The study area is an important industrial demonstration area for the government to promote the economic development of central China. It not only plays a demonstration role in economic development, but also plays a role in environmental protection efforts in order to achieve the sustainable development goals for the demonstration Area.

3.2 Analysis of the driving forces of eco-assets

3.2.1 Impact of changes in landscape pattern on eco-assets
Landscape pattern refers the spatial structure and features of land, which are the result of human activity and natural processes. The arrangement of different landscapes form a series of different sizes and shapes. Landscape pattern is the concrete manifestation of landscape heterogeneity and the result of various ecological processes. The most pervasive forms of landscape pattern are spatial plaques of different scales. Landscape pattern and changes to landscape pattern are a comprehensive reflection of the regional ecological environment system produced by the interaction of natural and man-made factors. The type, shape, size, quantity and spatial combination of landscape patches are the result of the interaction of various disturbances. the ecological processes and marginal effects in the region.
As shown in Table 3, the plaque area of cultivated land and grassland decreased, and the plaque area of construction land, forest land and water areas increased from 1990 to 2013; the corresponding PLAND index showed the same trends. As a general rule, the greater the NP index, the higher the fragmentation, the smaller the NP index, the lower the fragmentation. With regard to the PD and ED indices, the value increases and the landscape tends to be broken. In general, the degree of fragmentation of cultivated land, construction land, water areas and forest lands became greater and the integrity of the landscape was damaged during the years 1990 to 2013. The destruction of cultivated land, forest land, water areas was the main reason for the rapid reduction of land use types. Reduction of cultivated land was due, on the one hand, to the destruction of the ecological environment that resulted in desertification. On the other hand, it was due to infrastructure construction and economic construction on land formerly used for agriculture. The fragmentation of forest land was mainly the result of the expansion of urban construction. The area of forest land was significantly reduced, and even though urban systems have matured and the amount of urban green land area has increased, there has been an overall loss of eco-assets. The reduction of grassland was caused mainly by industrial pollution and the conversion of some grassland to construction land. Grassland also plays an important role in regulating climate, conserving water sources and conserving biodiversity, so the loss of grassland in the Wanjiang Demonstration Area represents a significant loss of eco-assets.
Table 3 Changes in the landscape pattern index from 1990 to 2013
Land type Year Total class area Percentage of landscape Number of patches Patch density Edge Density
Cultivated land 1990 4151868 53.3201 572 0.0073 4.0166
2000 4111100 52.7859 595 0.0076 4.1041
2013 4070920 52.2437 602 0.0077 4.0104
Construction land 1990 413168 5.3061 1247 0.0160 1.2841
2000 452760 5.8134 1309 0.0168 1.4016
2013 493332 6.3311 1203 0.0154 1.3274
Forest land 1990 2115036 27.1622 499 0.0064 2.5977
2000 2110724 27.1014 490 0.0063 2.6212
2013 2587396 33.2051 378 0.0049 2.4083
Water area 1990 537628 6.9045 531 0.0068 0.8846
2000 537824 6.9056 532 0.0068 0.8849
2013 630728 8.0944 902 0.0116 1.2151
Grassland 1990 568792 7.3047 711 0.0091 1.2722
2000 575652 7.3913 723 0.0093 1.2923
2013 2744 0.0352 9 0.0001 0.0090
Fig. 3 Changes in per capita eco-assets in the study area from 1990 to 2013
3.2.2 Effects of Population Factors on eco-assets
During the period from 1990 to 2013, the population of Wanjiang Demonstration Area increased by 2.81 million people, a growth rate of 34.05%. The largest population growth was in Hefei City, which increases by 1.10 million people, followed by Wuhu City, which increase by 0.62 million people. The change of eco-assets per capita is closely related to the total amount of eco-assets, and the total population in the region also reflects the interaction between humans and nature. According to Figure 3, Hanshan County had the largest change in per capita assets. During the years 1990-2000, the change of per capita eco-assets in the study area was the highest in this county, with a rate of change of 64.4%. The largest reduction of per capita eco-assets was in the Xuancheng urban area, with a rate of change of 91.01%.
3.2.3 Impact of Climatic Factors on eco-assets
Climate change directly affects temperature and precipitation and this has an impact on the quality of regional ecosystems. In addition, changes in meteorological factors such as light and moisture also have a significant impact on ecosystem productivity. A rise in temperature may also necessitate adjustments to planting structure. At the same time, a temperature increase also leads to a reduction of soil water content, and this can cause a decline in crop productivity and affect the region's eco-assets.

4 Conclusions

(1) The spatial distribution of eco-assets: the distribution of eco-assets in the study area is very uneven, with more assets in the south than in the north, and a gradual decrease from south to north. The central region has higher ecological assets than other regions, it declined first and then increased during the period 1990-2013. The high value area of eco-assets is distributed mainly in parts of Anqing and Chizhou. The southwest of the study area has high vegetation coverage and the Yangtze River accounts for most of the water areas in the study. Low value areas can be found in the Hefei urban area and surroundings.
(2) The eco-assets of cultivated land, grassland and water areas decreased, indicating that soil, water and grassland resources are seriously threatened. The increase of forest eco-assets was due mainly to the effective implementation of policies promoting the return of cultivated land to forests and advanced agricultural technology. In general, during the period from 1990 to 2013, the total growth rate of eco-assets in Wanjiang Demonstration Area was 3.05%, indicating a slight increase. Reductions in eco-assets were caused mainly by the expansion of construction land and transportation land area. The deterioration of the environment has reduced the value of eco-assets of various land use types, and this leads to the decrease of eco-assets.
(3) The change of ecological assets in Wanjiang Demonstration Area is the result of the interaction between the natural environment and human activities, including landscape pattern, population and climate However, human activities have played the leading role. Human activities affect ecological assets more directly and more quickly than does the natural environment, and the changes that result are more intense.

The authors have declared that no competing interests exist.

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