Temporal-Spatial Evolution of the Urban Ecological Footprint Based on Net Primary Productivity: A Case Study of Xuzhou Central Area, China

Abstract

The urbanization process all over the world has caused serious ecological and environmental problems which have recently become a focus for study. Ecological footprint analysis, which is widely used to assess the sustainability of regional development, can quantitatively measure the human occupation of natural capital. In this study, the ecological footprint based on net primary production (EF-NPP) and MODIS data were used to measure the ecological footprint in Xuzhou central area from 2005 to 2014. The results showed that from 2005 to 2014, the per capita ecological footprint increased from 1.06 to 1.17 hm²/person; the per capita ecological capacity decreased from 0.10 to 0.09 hm²/person; the per capita ecological deficit increased from −0.96 to −1.09 hm²/person; and the ecological pressure index increased from 6.87 to 11.97. The composition of the ecological footprint showed that grassland contributed most to the ecological footprint and deficit, and cultivated land contributed most to the ecological capacity. The spatial distribution of the ecological footprint changed significantly, especially in the expansion of the area of lower value. The ecological capacity and deficit changed little. The ecological situation in Xuzhou central area was unbalanced. Based on this study, Xuzhou city was recommended to control the increase of the ecological footprint, improve the ecological capacity and balance the ecological pattern for sustainable development.

1. Introduction

Since the Industrial Revolution, the rapid development of cities and countries has caused an ecological and environmental disaster that is directly threatening human survival and sustainable social development. With the rapid advancement of urbanization and the accelerated growth of urban populations per year, the demand for land and natural resources in production and life has increased rapidly, and a significant amount of cultivated land, forestland and other types of ecological land have been occupied for real estate [1,2]. The development and construction of commercial areas and industrial areas, the changes in land use, and especially the excessive spread of cities have had a negative impact on the ecosystem service function [3], by impacting on water [4,5], promoting urban climate change [6] and contributing to the destruction of biodiversity [7]. Urbanization has caused serious conflicts between humans and nature, and overload of the regional land ecological carrying capacity as well.

Similar to in other countries, after the reform and opening up, China’s urbanization level has increased from 17.92% in 1978 to 58.52% in 2017, with an average annual growth rate of more than 1%. The gross domestic product (GDP) of China has maintained an average annual growth rate of about 10% from the early 90s to 2011 [8], and this achievement has attracted worldwide attention. However, ecological problems have increased continually during the last 30 years, accelerating the depletion of resources and the environment that China’s economy and society rely on, and seriously hindering the dream of ordinary people to pursue a beautiful and livable life [9]. The government has also realized the seriousness of the deterioration of the ecological environment [10]. Therefore, to achieve sustainable development, accurately defining the land carrying capacity, rationally using land, and easing the contradiction between people and land are essential challenges to face, and this is a notable focus of research and policy innovation at present.

Compared with previous economic models, ecological footprint analysis can quantify the utilization of natural capital by human beings, evaluate the impact of human activities on the ecosystem and environment [11], and judge whether human activities are within the carrying range of the ecosystem. The higher the ecological footprint value, the more resources humans need, and the more severe impact on the environment and Earth. The ecological footprint method provides an evaluation method for the quantitative measurement of sustainable development [3]. The ecological footprint analysis method was formally proposed by Canadian eco-economist William Rees in the early 1990s, and his student Mathis Wackernagel refined the ecological footprint analysis in his following research [12,13]. By calculating the bio-productive land and water area consumption and output, ecological footprint analysis estimates the supply and demand of natural capital. Bio-productive land is the basis that provides a unified measurement for natural capital, and makes it easy to calculate the total output of different kinds of land [13]. Bio-productive land is the land or water that has biological production capacity and can be classified into six types: Cultivated land, grassland, forestland, water area, fossil energy land, and built-up land.

Ecological footprint analysis has been applied by various scholars in the measurement of ecological carrying capacity and the sustainable development level because it is easy to understand and simple to calculate [14,15]. With the increase in the breadth and depth of research, scholars have improved many aspects of the traditional ecological footprint model, including its time and space scales. Scholars have also studied the temporal variation and prediction of the ecological footprint, which makes up for the shortcomings in instantaneity of traditional ecological footprint analysis [16,17,18]. Some scholars have proposed modified models based on the national hectare, provincial hectare and local hectare, making the ecological model present the profit or deficit more precise on medium and small scales [19,20]. In recent years, some scholars have improved the calculation method of traditional ecological footprint analysis by utilizing knowledge from other areas. Others have proposed an ecological footprint model based on emergy analysis and net primary productivity (NPP) to obtain the equivalence factors and yield factors that reflect the real consumption and production situation [21,22,23]. Still others have introduced footprint depth and footprint size to construct a 3D ecological footprint model [24,25]. Overall, there is a mature structure of research on ecological footprint analysis. However, current researches paid less attention to the spatial evolution and spatial pattern of the ecological footprint, and more to the temporal change of the size of the ecological footprint. With the aim of addressing limitation of ecological footprint analysis in spatial analysis, we undertook this study.

In this study, in view of the characteristic ease of calculation, the ecological footprint based on net primary productivity (EF-NPP) was applied to calculate equivalence factors and yield factors. The aim of this article is to present the temporal change and spatial evolution of the ecological footprint in Xuzhou central area from 2005 to 2014, and to explore the spatial pattern of the ecological footprint and ecologically fragile areas, in order to optimize the spatial pattern of Xuzhou central area.

2. Study Area

Xuzhou city is located in Jiangsu Province, China and the latitude and longitude are 116°22′–118°40′ E, 33°43′–34°58′ N. The area of Xuzhou city is 1.18 × 10⁴ km², and the population was 8.76 × 10⁶ at the end of 2017. There are 10 districts, counties and county-level cities under the jurisdiction of Xuzhou city. Xuzhou central area is the center of Xuzhou city, which contains five districts (Yunlong district, Gulou district, Quanshan district, Jiawang district, and Tongshan district), covering an area of 3.06 × 10³ km². Figure 1 shows the location of the study area.

According to the Statistical Bulletin of Xuzhou City’s 2017 National Economic and Social Development [26], by the end of 2017, the GDP of Xuzhou was 6.61 × 10¹¹ yuan, and the urbanization rate was 63.8%, an increase of 1.4% over the previous year. However, the rapid urbanization process in Xuzhou has also caused some problems, such as the occupation of ecological land for urban construction land, the contradiction between supply and demand of construction land, and the weakening of land ecological service functions. These are urgent problems to be solved immediately and in addition, in a resource-exhausted city, many environmental problems also arise in the process of urban transformation.

3. Data and Methods

3.1. Data Sources and Pretreatment

3.1.1. Data Sources

According to its availability, the statistical data were obtained from the Xuzhou Statistical Yearbook from 2005 to 2014 [27], including the area, population of Xuzhou central area, and the consumption and yield of bio-productive land.

There are two kinds of MODIS data used in this study: Net Primary Production (MOD17A3) and Land Cover Type (MCD12Q1). The data are from Earthdata, NASA (https://earthdata.nasa.gov/) [28]. The MODIS Net Primary Productivity product (MOD17A3) defines the rate at which all plants in an ecosystem produce net useful chemical energy. The spatial resolution is 1 km × 1 km, the remote sensing parameters are from Terra satellite, and the calculation result is given in yearly production. The valid values of the MOD17A3 data range from 0 to 65500 and the scale factor is 0.0001. The MODIS Land Cover Type product contains five classification schemes, and the spatial resolution is 500 m × 500 m. In this study, the Land Cover Type 2 was selected to reclass the land use cover.

3.1.2. Data Pretreatment

The software MODIS Reprojection Tool (MRT) was used to reproject the MODIS data into Albers projection. ArcGIS was used to clip the grid files by the Xuzhou central area boundary and China boundary. MOD17A3 data were processed to obtain the NPP value and MCD12Q1 data were processed to reclass the land use cover into cultivated land, forestland, grassland, water area and built-up land. Finally, MOD17A3 data and MCD12Q1 data were analyzed by the overlay analysis function in ArcGIS to obtain the spatial distribution of the ecological footprint.

3.2. Research Methods

3.2.1. Net Primary Productivity

NPP is defined as the rate of atmospheric carbon uptake through the process of net photosynthesis minus dark respiration [29,30]. As the most important part of the surface carbon cycle, NPP can not only directly reflect the productivity of plant communities in the natural environment and show the quality of the terrestrial ecological system but also can define the main factor of the carbon source/sink and the process of regulating ecosystem [31]. The recent research on NPP has mainly focused on the measurement of NPP and the calculation model of NPP, and some research has undertaken the dynamic simulation of regional NPP [32].

3.2.2. Ecological Footprint Model

The ecological footprint model is divided into two parts: The ecological footprint and ecological carrying capacity. The formulas are as follows [12,33]:

$$EF=N\times ef=N\times {\displaystyle \sum }_{i=1}^6\left({\lambda }_i \times A_I\right)=N\times {\displaystyle \sum }_{i=1}^6\left({\lambda }_i \times {\displaystyle \sum }_{j=1}^{n}a{a}_j\right)=N \times {\displaystyle \sum }_{i=1}^6\left[{\lambda }_i \times {\displaystyle \sum }_{j=1}^n\left(\frac{c_j}{p_j}\right)\right].$$

(1)

where EF is the total ecological footprint (hm²); N is the total population; ef is the per capita ecological footprint (hm²/person); i is the six types of bio-productive land and water area; λ_i is the equivalence factor of i-type bio-productive land; A_i is the per capita area of i-type bio-productive land (hm²); j is the type of consumption item; aa_j is the per capita area of the j-th bio-productive land (hm²/person), c_j is the per capita annual consumption of j-th consumption item (kg/person); and p_j is the average production capacity of the j-th consumption item (kg/hm²).

$$EC=N\times ec=N\times {\displaystyle \sum }_{i=1}^6\left({\alpha }_i \times {\lambda }_i \times y_i\right)$$

(2)

where EC is the total ecological carrying capacity (hm²); N is the total population; ec is the per capita ecological carrying capacity (hm²/person); a_i is the per capita area of i-type bio-productive land (hm²); λ_i is the equivalence factor of i-type bio-productive land; and y_i is the yield factor. According to the suggestion that the United Nations World Commission on Environment and Development (WCED) proposed in the book Our Common Future, to protect biodiversity, the ultimate ecological carrying capacity should be deducted by 12% on the basis of the balanced ecological carrying capacity [34].

In comparing the ecological footprint and ecological capacity, if the ecological footprint is higher than the ecological capacity an ecological deficit is created, which means under the current technology and productivity, the area of bio-productive land cannot support human life. Otherwise, an ecological profit occurs, which means the area of bio-productive land can adequately support human life.

According to the production of the study area and the availability of data, the consumption items were classified as shown in

Table 1. Consumption items of the national hectare ecological footprint model.

Bio-Productive Land	Consumption Item Type
Cultivated land	cereals, beans, potatoes, cotton, oilseeds, sugar, vegetable and melons, hemp, tobacco
Forestland	silkworm cocoons, fruits, chestnuts, ginkgo
Grassland	pork, beef, lamb, poultry, rabbit, milk, sheep, eggs, honey
Water area	aquatic products
Fossil energy land	coal, oil, natural gas
Built-up land	electricity

.

In the calculation of the production and consumption of bio-productive land, emergy conversion coefficient was used to convert the production and consumption into emergy [35], in order to make the calculation both simple and more accurate.

3.2.3. EF-NPP

After the invention of ecological footprint analysis, some scholars suggested that the consumption of natural capital in ecological footprint analysis is actually the occupation of NPP [36]. By integrating NPP into the ecological footprint framework, EF-NPP was proposed by Venetoulis and Talberth in 2008 [21]. They refined the ecological footprint by changing the equivalence factors to NPP rather than agricultural productivity in order to achieve a more precise ecological footprint. In contrast with the traditional ecological footprint, in EF-NPP, when calculating the ecological capacity, we use a deduction of 13.4% to protect biodiversity.

The equivalence factor is the coefficient that converts the bio-productive land into areas with the same ecological productivity, and the yield factor is the coefficient that describes the yield difference between the study area and the nation overall. The equivalence factor and yield factor in EF-NPP can show the different productivity of different land types or different areas directly. According to earlier researches, the formulas of the equivalence factor and yield factor are as follows [36,37]:

$${\lambda }_i=\frac{NP{P}_i}{NPP}$$

(3)

where λ_i is the equivalence factor, NPP_i is the average NPP of i-type bio-productive land in the study area, and NPP is the average NPP of all types of bio-productive land in the study area.

$$y_i=\frac{NP{P}_i}{\overline{NP{P}_i}}$$

(4)

where y_i is the yield factor, NPP_i is the average NPP of i-type bio-productive land in the study area, and $\overline{NP{P}_I}$ is the average NPP of i-type bio-productive land in China.

3.2.4. Ecological Pressure Index

The ecological pressure index refers to the ratio of the per capita ecological footprint and the ecological capacity, which represents the pressure tolerance of the regional ecological environment [38,39,40]. The formula is as follows:

$$EP=\frac{EF}{EC}$$

(5)

where EP is the ecological pressure index, EF is the ecological footprint, and EC is the ecological capacity. According to Zhao’s study, the ecological pressure index can be divided into six grades [38], as shown in

Table 2. Ecological pressure index.

Grade	Ecological Pressure Index	Token State
1	< 0.50	Very safe
2	0.51–0.80	Relatively safe
3	0.81–1.00	Slightly unsafe
4	1.01–1.50	Relatively unsafe
5	1.51–2.00	Very unsafe
6	> 2.01	Extremely unsafe

.

4. Results and Analysis

The ecological footprint in Xuzhou central area was analyzed in two aspects: Temporal evolution and spatial evolution.

4.1. Temporal Evolution of Ecological Footprint in Xuzhou Central Area

4.1.1. Calculation of Equivalence Factors and Yield Factors

To calculate the temporal evolution of the ecological footprint, first the equivalence factors and yield factors were calculated using the consumption and yield of bio-productive land, as shown in Figure 2.

As shown in Figure 2a, the equivalence factor of cultivated land was the highest, and that of the water area was the lowest. The results mean that the bio-productive capacity of cultivated land in Xuzhou central area was the highest in the bio-productive land and that of the water area was the lowest. The equivalence factor of fossil energy land was the same as forest land because the fossil energy footprint was expressed by the area of the forest which can absorb CO₂ emissions.

As shown in Figure 2b, the yield factor of grassland was the highest and that of forestland was the lowest. The results mean that the bio-productive capacity of cultivated land and grassland in Xuzhou central area were higher than the national average level, while the bio-productive capacity of forestland, the water area, and built-up land were lower than the national average level. There were fluctuations during the study period but the changes were small. The yield factor of fossil energy land was zero because there is no bio-production output.

4.1.2. Calculation of the Ecological Footprint and Ecological Pressure Index

The per capita ecological footprint, ecological capacity and ecological deficit in Xuzhou central area from 2005 to 2014 were measured as shown in

Table 3. Temporal change of the per capita ecological footprint profit and deficit in Xuzhou central area from 2005 to 2014 (hm²/person).

Year	Ecological Footprint	Ecological Capacity	Ecological Deficit
2005	1.0617	0.1004	−0.9613
2006	0.9880	0.1153	−0.8728
2007	1.0387	0.0903	−0.9484
2008	0.9432	0.1208	−0.8225
2009	1.0809	0.1084	−0.9725
2010	1.1164	0.1239	−0.9925
2011	1.1723	0.1132	−1.0591
2012	1.1766	0.1202	−1.0564
2013	1.2441	0.1157	−1.1284
2014	1.1718	0.0865	−1.0854

.

As shown in Table 3, from the general view, the per capita ecological footprint showed a rising trend of 0.1101 hm²/person. There were fluctuations during study period which may be caused by the deduction of consumption and equivalence factors. The ecological footprint reached its highest point of 1.2441 hm²/person in 2013, and the equivalence factors of forestland, grassland, water area, fossil energy land and built-up land both increased. The per capita ecological capacity decreased from 0.1004 hm²/person to 0.0865 hm²/person. The per capita ecological profit and deficit presented as the ecological deficit from 2005 to 2014, which increased by 0.1241 hm²/person. The fluctuation trend of ecological deficit is basically the same as ecological footprint.

The ecological pressure index represents the pressure tolerance of the regional ecological environment. The ecological pressure index of Xuzhou central area was calculated and the results are shown in Figure 3.

As shown in Figure 3, the change of the ecological pressure index from 2005 to 2014 presented with a rising trend, although there were declines in 2006, 2008, 2010, and 2012. It is worth noting that the ecological footprint and ecological capacity both decreased in 2014, however the ecological pressure still increased. The reason for this situation was that the decreasing rate of the ecological footprint was smaller and that of the ecological capacity was bigger, which led to the overall increase of the ecological pressure. According to the grade of the ecological pressure index, the ecological situation of Xuzhou central area was extremely unsafe from 2005 to 2014.

4.1.3. Composition of the Ecological Footprint in Xuzhou Central Area

To analyze the temporal change of the ecological footprint in Xuzhou central area more accurately, we studied the composition of the ecological footprint, ecological capacity, and ecological deficit from 2005 to 2014.

As shown in Figure 4, the grassland ecological footprint contributed the most to the whole ecological footprint during the study period, and the proportion increased from 31% to 40%. The cultivated land ecological capacity took the largest proportion, which was over 80%. The proportion of the grassland ecological deficit which took the largest proportion, increased from 34% to 43%, while the forestland ecological deficit decreased from 16% to 7%. The ecological footprint, ecological capacity and ecological deficit of water area changed little, which meant that the humans’ impact on water were smaller.

4.2. Spatial Evolution of Ecological Footprint in Xuzhou Central Area

The spatial pattern of the ecological footprint, ecological capacity and ecological deficit in the main years during study period are shown in Figure 5. The spatial pattern of the whole study period are shown in Figure A1.

As shown in Figure 5a, the green color represents a lower ecological footprint value, and the red color represents a higher value. We can see that the ecological footprint values of built-up land were relatively low, and the ecological footprint values of the water area were higher. It can be seen that in 2005, 2007, and 2008, the ecological footprint values of Xuzhou central area were relatively low, mainly concentrated between 0.08–0.12 hm²/person, and the pattern was superior. In 2006, 2009, 2011, 2012, 2013, and 2014, the ecological footprint values of the central, southwestern, and northeastern parts of Xuzhou central area were relatively low. The low value area expanded toward the east and northeast over time. In these years, ecological footprint values between 0.12–0.18 hm²/person accounted for a large proportion of the total. In 2010, the overall ecological footprint of Xuzhou central area increased, and the pattern deteriorated. From the evolution of the ecological footprint we can find that humans’ impact on nature became obvious and serious.

As shown in Figure 5b, the spatial pattern of the ecological capacity changed little during the study period. As can be seen from the legend, red indicates a low ecological carrying capacity and green indicates a high ecological carrying capacity. The lower values were concentrated in the northern boundary, center, northeast and southwest parts of Xuzhou central area, and the higher values were distributed in the northwest and southeast of Xuzhou central area. The reason why the ecological capacity in the center was lower was that there was built-up land mainly and humans’ activities were more frequent.

As shown in Figure 5c, the spatial distribution of the ecological deficit changed little, in accordance with the ecological capacity. The values were mainly concentrated between −0.04 to 0 hm² except in 2014, when the value was concentrated mainly between −0.08 to −0.04 hm². The ecological deficit increased in 2014, meaning that the ecological environment deteriorated further. The higher values of the ecological deficit were distributed in the northeast and southwest of Xuzhou central area and the lower values were distributed in the northwest and southeast.

5. Discussion

5.1. EF-NPP and Traditional Ecological Footprint Analysis

Recently, near real-time MODIS GPP/NPP products have been used in global or regional studies more and more [17,41]. EF-NPP is an improvement on traditional ecological footprint analysis. The main difference is the calculation method of the equivalence factors and yield factors. EF-NPP calculates the factors by the NPP of different kinds of land, while the traditional ecological footprint calculates by the consumption and yield of bio-productive land. Other than this, EF-NPP can calculate the factors of built-up land, in order to better express the productivity [22,36,37].

Compared with the study published in 2014, which also focused on the ecological footprint of Xuzhou [42], the ecological footprint and ecological capacity values of this study were relatively low, as shown in Figure 6. The main reasons for the difference are the different equivalence factors and yield factors. The cultivated land and forestland equivalence and yield factors of this study were both lower, thus led to the low ecological footprint and low ecological capacity values. From both results we can see that the ecological footprint of Xuzhou increased during the study period, so it is important to establish a reasonable ecological footprint control mechanism in order to improve the ecological carrying capacity, and control and reduce the ecological deficit. As far as the composition of the ecological capacity, it is necessary to optimize the structure of the ecological capacity, and improve the grassland, forestland, and built-up land ecological capacity.

Compared with the ecological footprint of the whole of China measured by EF-NPP [43], we found that the ecological footprint and ecological capacity of Xuzhou central area were both lower than the average value of China. As shown in Figure 7, the equivalence factors of cultivated land, forestland, built-up land, and fossil energy land in Xuzhou were lower than the average level of China, meaning the NPP of these bio-productive land in Xuzhou were relatively low. Additionally, the yield factors of cultivated land, forestland, built-up land, and fossil energy land in Xuzhou were lower than the average level of China, meaning the NPP of these bio-productive land did not reach the average level.

Currently, there is still no standard framework for ecological footprint analysis, and the existing studies of ecological footprint analysis have paid less attention to the relationship between economic development and the ecological environment [44,45]. Ecological footprint analysis will be improved in the future to measure the natural capital more accurately and more comprehensive.

5.2. Ecological Footprint Spatial Pattern and Ecological Pressure

Some researchers hold the view that the ecological footprint cannot express the true ecological pressure [45,46]. However, in this study, the ecological footprint spatial pattern was showed, from which we could find where the ecological footprint was higher and the ecological capacity was lower in Xuzhou central area. The ecological pressure can be identified by the values of the ecological footprint and ecological capacity. According to the WWF’s report about China’s ecological footprint, China’s ecological footprint depends on the urbanization level [47]. It can be seen from the results that in the southwest and center parts of Xuzhou central area, with its high urbanization level, there was high ecological pressure. From the spatial pattern of the ecological footprint, the unbalanced ecological pattern should be optimized. The ecological pressure in the southwest and center of Xuzhou central area needs to be released.

However, there still remain some shortcomings in this study. Due to the availability of the MOD17A3 data, we could only measure the ecological footprint of Xuzhou central area until 2014. Additionally, the resolution of the MODIS data is relatively coarse.

6. Conclusions

During the process of urbanization, it is important to measure the human occupation of nature and maintain the sustainable development of society. Using EF-NPP, this article theoretically improved the shortcomings of the ecological footprint model in spatial analysis, quantitatively measured the temporal change of the ecological footprint and spatially located the ecologically fragile areas. The results of this article prove that the ecological footprint can be used to indicate the pressure humans put on nature, by comparing it with the ecological capacity. Based on the results we found, policy suggestions for the sustainable development and ecological civilization of Xuzhou city were proposed. The main conclusions of this article are as follows:

(1) The natural capital that humans require in Xuzhou central area increased, such that the bio-productive land could not support the demand of human living and production activities, and the ecological situation became extremely unsafe.

(2) The spatial pattern showed the ecologically fragile areas and the unbalanced ecological situation in Xuzhou central area. The ecological pressure was higher in the northeast and southwest of Xuzhou central area.

(3) Policy measures should be adopted to promote the harmonious development of ecology and the economy. The government should control the increase of the ecological footprint and improve the ecological capacity in the center of Xuzhou to alleviate conflicts between humans and the land. The urban space in different areas should be optimized to achieve the comprehensive and coordinated development of Xuzhou central area. The government should pay attention to increasing the investment in ecological civilization construction, improving the ecological environmental protection system as soon as possible in order to coordinate the development of the social economy and ecological environment, and take the road of sustainable development. The EF-NPP could be applied in regional ecological environment monitoring, and has profound implications for ecological security and city development planning.

(4) The EF-NPP model measures the equivalence factors and yield factors by NPP instead of the production and consumption, which avoids deviation in the calculation. Combining the calculation values with land use data can spatialize the ecological footprint, ecological capacity and ecological deficit, thus making up for the shortcomings in the spatial analysis of ecological footprint analysis.

(5) In future studies, the accuracy of land use data needs to be improved. For example, the MODIS data could be replaced by Landsat data with a higher resolution. Furthermore, the ecological footprint model can continue to be improved to be more comprehensive.