1. Introduction
Ecosystem services are the welfare and advantages that humans derive from ecosystems, such as supply, regulation, support, and cultural services [
1,
2,
3], which directly or indirectly support human survival and development [
4]. With the rapid socioeconomic growth worldwide, the impact of human activities on the ecological environment has been intensified, and the ecosystem has been repeatedly damaged [
5]. Ecosystem service value (ESV) is a quantitative evaluation of ecosystem service function, and the study of ESV can measure the ecological condition of a region, which is important for the conservation, restoration and sustainable development of regional ecosystems.
Costanza et al. (1997) conducted the first study on estimating the value of global ecosystem services and natural capital [
1]. It provided theoretical and methodological support for the measurement of the ESV. The current research methods for ESV calculation, which include the market-price method, the shadow-engineering method, the hedonic-price method, the hydrological- and water-quality-modeling method, and the willingness-to-pay method, have been applied to ecological resources, planning, construction and management, government policies and so on [
6,
7,
8,
9,
10,
11]. They are more accurate in assessing a single ecosystem service but lack comparability and applicability. Additionally, the equivalent factor method is more prominent in reflecting the change pattern and mechanism of action of ESV [
12,
13,
14]. It has a wide range of applications and is highly applicable. The Chinese scholars Xie et al., based on the method of calculating of the unit-area-value-equivalent factor, obtained relevant expert knowledge based on the model proposed by Costanza et al. and modified the global ESV-equivalent factor by combining it with the actual ecological and environmental conditions in China to make it more consistent with the actual conditions in China [
15,
16].
The calculation of the ESV measures the quality of ecosystem services in a region. It is a monetized representation of ecosystem services. It can help governments to understand the general state of ecosystems [
17,
18]. However, it does not reflect the drivers that influence ecosystem service functions. It leads to the inability to analyze the specific causes of ecosystem destruction at the root cause. Therefore, it is also crucial to study the factors that influence the ESV. The ESV is directly or indirectly influenced by factors both internal and external to the ecosystem. Among them, natural factors have direct impacts on the ESV within the ecosystem [
19]. Studies have shown that the elevation, slope, and direction of the terrain affect ecological service functions such as soil and water conservation, raw material production, and water-supply capacity [
20]. Climate influences plant growth and enables changes in ecosystem services through the regulation of surface water and heat conditions [
21,
22]. The growth activities of organisms and the spatial characteristics of habitats influence ecosystem service functions such as food production and the maintenance of biodiversity [
23,
24]. Additionally, as human activities intensify, the impact of anthropogenic factors on the ESV become more prominent [
25,
26]. Population density, socioeconomic activities, and malicious destruction of the environment all have important effects on the ESV [
27,
28].
The study region’s natural surroundings in the Loess Plateau, with low annual precipitation, low vegetation cover, steep terrain, loose soils, and the constant disturbance of human activities, have caused a highly vulnerable biological environment to develop, with land desertification, soil erosion, and salinization. Zhang et al. analyzed the extent to which land-use change has an impact on the ESV as well as the coordination between ecological and environmental quality and socioeconomic development [
29]. Jiang et al. used a mix of benefit transfer and proxies for land-use and land cover to study the ESV resulting from changes in the land-use and land cover on the Loess Plateau between 1990 and 2015 [
30]. Fang et al. examined and evaluated the connection between the ESV and land-use patterns, as well as assessing the association between land-use change and the ESV at the town scale [
31]. Therefore, in the Loess Plateau, studies on ecosystem services have mainly focused on analyzing the effects of land-use/cover changes on the ESV within the Loess Plateau region, while fewer studies have been conducted to examine the mechanisms, quantify the effects of various environmental and societal factors on the ESV, and forecast future trends in the field. In this study, based on the investigation of the ESV distribution and change in the Loess Plateau of Northern Shaanxi from 2000 to 2020, the influence status of multiple factors on the ESV was focused on and the future development trend was predicted. The objective of this study is to address the following questions: (1) What are the ESV’s temporal trends and regional distributions in the Loess Plateau of Northern Shaanxi from 2000 to 2020? (2) What is the degree of influence of various factors on the ESV in the Loess Plateau of Northern Shaanxi? (3) What is the status of the integrated constraints on ecosystem development within the Loess Plateau of Northern Shaanxi? (4) What is the future development trend of the ecological environment of the Loess Plateau in Northern Shaanxi?
4. Discussion
4.1. Temporal and Spatial Change Mechanism of the ESV
In this study, we found that there were significant temporal dynamics and spatial heterogeneity of the ESV in the Loess Plateau region of Northern Shaanxi. This region has seen a large change in land-use status in the last 20 years, and this has led to changes in the ecosystem services of the region and their values. Construction land is a nonecosystem service site and therefore has a null ESV [
58,
59,
60]. Additionally, within the region from 2000 to 2020, the ESV has been decreasing with increasing construction land and cropland. Numerous studies have found that urban expansion and the increase in cropland come at the cost of high-ESV lands such as forestland and grassland [
61,
62]. These lands occupy and affect other ecological lands, leading to the decrease in the ESV. This is consistent with the results of our study. Additionally, in our study, the ESV in the study area showed a trend of being high in the south and low in the north. After the analysis, it was found that Northern Shaanxi is a relatively rich region of coal resources in China, and coal resources are more concentrated in the northern part of the study area, near Shenmu City, Fugu County, Yulin City, etc. The concentrated coal mining has caused damage to the surrounding ecological environment to some extent. Qian et al. found that mining activities in the southern Qilian Mountains caused significant ESV losses to the grassland and wetland [
63]. Gao et al. found that the dramatic expansion of mining land had destroyed large areas of forestland and reduced the ESV [
64]. The southern part of the study area, Huanglong County, is one of the eight major forest areas in China. It is also a protective forest area of the Loess Plateau. The proportion of forestland in the area was above 85% in all years, and the vegetation grows vigorously. The study of this region is important for the conservation of regional biodiversity and the maintenance of ecological balance [
65]. Therefore, the ESV was higher in the southern part of the study area. In addition, the spatial autocorrelation model was used to analyze the spatial aggregation pattern and association pattern of the ESV, which can further reveal the spatial differentiation characteristics of the ESV in the study area [
66]. In this study, a high-high aggregation area in the south and a low-low aggregation area in the northcentral part were identified, respectively. This indicates that the ESV in the study area has obvious spatial aggregation characteristics.
4.2. Influencing of Various Factors on the ESV
The constant changes in the ESV are influenced by multiple natural and social factors [
67,
68,
69]. In this study, the effect of each factor on the regional ESV was found to be negatively correlated with population density and the ESV. The effect of soil type on the ESV was determined by the nature of the soil itself. The other five factors were positively correlated with the ESV. These findings are consistent with previous studies [
70,
71]. Analysis of the weight of each factor on the ESV using the entropy weighting method revealed that population density, rainfall, and soil type in the study area have a greater effect on the ESV, and the distance from a road has the least effect. Human activities disturb local ecosystems, altering the ecological environment and affecting ecological functions, leading to a decrease in the ESV. Guo et al. found that population density was the most important factor influencing the ESV in the region of Funiu Mountain [
72]. In addition, areas with high rainfall have good hydrothermal conditions that are more suitable for vegetation growth and have more complex ecosystems. Meanwhile, low rainfall causes the ecological function of the area to be weakened. Xie et al. found that the ESV in China gradually decreased from the rainfed southeast to the arid northwest [
73]. Zhao et al. found that precipitation has an important impact on ecosystem services in the Yangtze River Delta region [
74]. In this study, although roads are also the result of human production and construction, they only have a small impact on the ESV in a limited area of their proximity due to the limitation of their own functional performance. Therefore, the degree of impact is relatively small. After a comprehensive evaluation by using the weights of each factor, it was found that the ESV was high in the areas with a low impact and low in the areas with a high impact in the study area. This indicates that the ESV is higher in areas with abundant precipitation, sufficient sunshine, high elevation, a gentle slope, and low human intervention. However, excessive human intervention can affect ecosystem function [
75]. Therefore, if the various factors mentioned above are adjusted in the future, a good ecological environment in the study area can be maintained.
4.3. Trend Forecast Analysis of the ESV
Forecasting of the regional ecological environment enables us to anticipate the future development trend of the ecological environment. Forecasting furthers our understanding of the regional ecological security situation in order to facilitate constructive suggestions for ecological environment improvement and protection [
76]. CA models have powerful computational capabilities to solve complex system problems and have been widely used in land-use [
77,
78]. However, it is difficult for a single model to achieve a reasonable prediction of land-use change. Some scholars have coupled the CA model with logistic functions, artificial neural network models, and SD models to carry out research on the dynamic prediction of land-use [
79,
80,
81]. However, the above integrated models are difficult to achieve in terms of nonlinear representation, parameter optimization, operability, and so on [
82,
83,
84]. However, the CA–Markov model is more scientific and applicable. It can make the prediction results more accurate [
85]. In this study, the CA–Markov model was used to impose the corresponding constraints to achieve the prediction of land-use in the study area and calculate the ESV. The results show that the ESV of the study area will decrease by 2030. This is mainly due to the continuous increase in construction land. Therefore, further rational planning of each land-use type is needed to promote the improvement of ecological service quality.
4.4. Policy Implications
First, after the analysis, we found that human activities have the strongest influence on the ecological environment within the Loess Plateau area in Northern Shaanxi. Therefore, in order to further control the interference of human activities, we need to establish reasonable ecological protection zones within the study area. Human activities are restricted within the protected areas to protect the ecological environment and biodiversity. Meanwhile, in regional territorial spatial planning, three control lines of the ecological protection red line, permanent basic agricultural land, and urban development boundary should be determined. The government should develop the regional economy and ecological security at the same time so as to coordinate regional development and ecological stability and prevent economic development at the expense of ecological environment [
86].
Second, according to the results of the comprehensive zoning evaluation of each impact factor, the zoning is based on the degree of impact. Different environmental improvement measures were implemented in the study area for different impact zones. The extremely heavy-impact area and heavy-impact area are mainly located in the northcentral part of the study area. This area is characterized by a steep terrain, strong human interference, and relatively fragile ecological environment. Therefore, the utilization rate of construction land and vegetation coverage should be further improved in this area, and ecological protection projects should be vigorously carried out. Thus, the stability and health of the ecosystem should be maintained. For the moderately and lightly affected areas distributed in the south, we should continue to do a good job of protecting the ecological environment of the area, controlling large areas of unreasonable grazing, and protecting water resources.
Third, Northern Shaanxi is extremely rich in mineral resources. However, extensive mining activities have caused groundwater pollution, surface landscape fragmentation, ground subsidence, soil quality decline, and other environmental problems [
87]. Measures should be taken to protect and restore the ecological environment of mining areas. Hu et al. proposed measures alongside mining to restore the ecological environment of the mining area [
88]. Bi et al. proposed the use of microorganisms to improve the quality of the soil in the mining area [
89]. Therefore, the corresponding methods for the ecological management of mining areas need to be proposed according to the mining characteristics of the study area so that the ecological condition of the entire Northern Shaanxi Loess Plateau can be improved.
4.5. Limitations and Future Work
The findings of this study offer some reference value for the future sustainable development and ecological environment of the region; however, there are some limitations to this study. The differences between different regions were affected by natural, social, and economic factors. In this study, the ESV’s equivalent factor was revised by calculating regional and national climate productivity, which is not comprehensive enough. In addition, in analyzing the factors affecting the ESV, this study selected annual rainfall, population density, roads, and other factors for analysis. Although both natural and social factors were included, the consideration of the factors still had some limitations. Therefore, there will be some differences between the established impact zone and the actual situation. Finally, when using the CA–Markov model for trend forecasting, the elevation, slope, water bodies, distance from the road, and distance from a water body were added, and the policy factors for future development in the area were not fully taken into account. Combined with the model itself being restricted, there will be some differences between the predicted results and the actual development in the future.
5. Conclusions
In this study, the temporal and spatial changes in the Loess Plateau of Northern Shaanxi based on the calculation of the ESV were analyzed, and an impact zoning map was established by quantifying various influencing factors. Finally, the future development trend of the ESV was predicted. The following conclusions can be reached: (1) The land-use types were mainly grassland, forestland, and cropland, and the combined area of the three types covered more than 95% of the area. In addition, construction land in the study area increased the fastest, with a 4.6-fold increase from 2000 to 2020. (2) From 2000 to 2020, the ESV decreased continuously, and a pattern of being high in the south and low in the north was evident in the spatial features. (3) The weighting analysis of influencing factors showed that population density (0.309) > rainfall (0.165) > soil type (0.116) > slope (0.109) > elevation (0.106) > annual average temperature (0.100) > and distance from a road (0.096). By establishing the impact zones, it was found that the degree of impact decreases from south to north in the area. (4) It is predicted that the ESV will remain reduced by 2030 compared to 2020 in the area.
The ESV is affected by a combination of factors. Natural factors create the foundation of the ecosystem, and with rapid socioeconomic development, humans will continue to impose on this foundation, making the ecosystem more and more unstable. Positive human behaviors lead to stronger ecosystem functions, while negative human behaviors disrupt the ecological balance and cause the ecosystem to evolve in an unsustainable direction. In this study, the factors that influence the ESV were considered and different impact areas were classified to understand the regional ecological quality, identify the root causes that limit the function of ecosystems, and predict the future development trend. The research results provide a scientific basis for ecological environmental protection and policy formulation in the Loess Plateau of Northern Shaanxi.