1. Introduction
Vegetation changes have recorded the imprint of human activities profoundly [
1]. Human activities such as land use transformation directly change the structure, process and function of ecosystems [
2,
3,
4]. In human activity areas, vegetation has been lost or altered for human use (e.g., commercial development and infrastructure construction), and this poses a major threat to biodiversity conservation [
5]. Net primary productivity (NPP) is defined as the accumulation rate of organic matter by vegetation, which is equal to the difference between the carbon absorbed by plant photosynthesis and the carbon consumed by plant autotrophic respiration [
6,
7], and it plays an important role in global carbon balance [
8]. Land use changes have had a wide and significant impact on the ecological environment, especially in urban agglomeration where urban expansion is one of the main driving forces of change in NPP [
4,
9]. So, the temporal and spatial distribution characteristics of dynamic changes of land use and NPP have become an important research content in regional eco-environmental assessment.
The urbanization process in metropolises may offset the positive effects on NPP [
3,
10]. Vegetation destruction and improper land use caused by human activities have caused serious land degradation and ecological environment problems [
11]. However, Li, X. [
7] found that the NPP of new urban land in 2019 was better than that of original urban land before 2010. The human activities, mainly ecological restoration projects, made the vegetation coverage on the Loess Plateau show a significant upward trend in the past three decades [
12]. As a metropolitan center, Beijing City is the capital of China with great land use transformations which is worthwhile researching. Discussing the land use transformation on the influence of vegetation NPP and whether the future changes are consistent are essential for alleviating the conflicts between sustainable development and environmental protection.
Previous studies of NPP have mainly focused on the two parts. The first part is the establishment, application and optimization of the NPP calculation model [
13,
14]. The other part is exploring the response mechanism of NPP by taking climate factors and human activities as the main driving factors [
15,
16]. Meanwhile, the change trend and the future development of NPP are also worth studying. The combination of Theil-Sen Median trend analysis and Mann–Kendall test is used to detect the trend of spatial variation in NPP widely [
7,
17]. This combination can eliminate the noise of original data and are very robust [
17]. Brilli, L. [
18] predicted a decrease in net ecosystem exchange and NPP by approaching the most extreme climate conditions. Sun, G. [
19] assessed the characteristics of NPP due to future climate change and CO2. These simulation results are realized by predicting the driving factors of NPP instead of the NPP itself. Other scholars simulate NPP in the future through the change trend of NPP in the past [
20,
21,
22]. In addition to analyzing the changing trend of NPP and its driving factors, it is necessary to study the future trend of them during rapid urbanization.
To predict the future land use (one of the driving factors of NPP), many kinds of land use simulation models have been developed, such as cellular automata (CA) [
23,
24,
25,
26], conversion of land use and its effects modeling framework (CLUE) model and its improved model [
27,
28,
29], future land use simulation (FLUS) model [
30] and patch-generating land use simulation (PLUS) model [
31,
32]. However, the CA model is weak at revealing the underlying drivers of land use change [
33]. CLUE-S model leads to the separation of the macro land use demand projections and the local change allocations [
34]. Thus, there is an urgent need for more comprehensive approaches to predict the land use in Beijing. At present, in order to pursue high accuracy, the mainstream of land prediction models has been the coupling model to eliminate the limitations of a single model by carrying out the simulation from two aspects: quantity and spatial distribution. The PLUS model has been proven to be a more effective model, which provides more precise simulation results than the FLUS model [
31]. A Markov chain predicts dynamic variation characteristics and is characterized by both high operational precision and high prediction accuracy [
30]. This paper used a Markov chain to predict the amount of land use and simulated spatial changes by PLUS model on the basis of physiographic driving factors, transportation driving factors and socioeconomic driving factors. In addition, researchers have evaluated the future spatiotemporal land use under different scenarios combined with simulation models [
24,
30,
31,
35]. In this research, different transition matrix restricted different types of land use transformations to obtain different scenarios.
Based on mathematical analysis methods such as unary linear regression, Getis-Ord Gi* index and Hurst index, the objectives of this study were to: (1) explore the spatiotemporal variation trend of vegetation NPP from 2000 to 2020 based on land use; (2) evaluate future land use at 30 m spatial resolution under three different scenarios in 2030; (3) analyze the future trend of NPP. The temporal and spatial variation in land use and NPP were comprehensively analyzed for ecological protection and management in this research. What is more, based on the impact of land use on vegetation NPP, the correctness of NPP change trend in the future can be judged. This research is expected to provide a scientific basis for spatial development plan and represent a valuable reference of the urban agglomeration similar to Beijing.
4. Discussion
4.1. Spatial Development Plan
In the twenty-first century, preparing cities for urban land use planning is a critical challenge, and the relevant authorities require guidance from the simulation results to define adaptation strategies and policies. In accordance with “The Master Plan of Beijing (2016–2035)” by The People’s Government of Beijing City, natural resources such as green space, water system and wetland are important ecological barriers and great attentions is attached to the protection of this famous historical and cultural city, therefore, these zones are the planning constraints zones in this study. The development area is also obtained from the centralized construction area in the released “planning map of two lines and three districts in the city”. Compared with the current land use situation, areas of the north of Daxing District, areas around Beijing Daxing International Airport and so on will be intensively constructed.
According to “The Master Plan of Beijing (2016–2035)”, the total scale of construction land (including urban and rural construction land, special land, external transportation land and some water conservancy facilities land) should be controlled within 3720 km2 by 2020; the amount of cropland would be no less than 1.66 million mu by 2020; the city’s forest coverage rate would increase from the current 41.6% to 44% by 2020. In the actual land use in 2020, the area of impervious surface was 3475.76 km2; the area of cultivated land was 3902.51 km2 (5.85 million mu); and the area of forest land was 7388.60 km2 (45.07%). The current regional development met the planning requirements, that is to say, the future development guidance of this study can refer to the land development planning.
From 2000 to 2010, the NPP value of vegetation in Beijing fluctuated greatly (
Figure 5). Then China has implemented a series of ecological forestry projects, such as Grain for Green Program, the Three-North Shelterbelt Project, Wildlife Protection and Nature Reserve Development Program around Beijing which have made remarkable achievements in vegetation restoration and ecological system construction [
21,
52].The future work plan is to establish an ecological restoration support mechanism by strengthening the ecological restoration of cropland forest network and river lake wetland in plain areas, and go on carrying the ecological forestry projects to continuously improve the quality of ecological space.
4.2. Review of Land-Use Simulation Results
The change of impervious surface area is the most obvious under three different scenarios, which is the main feature of land use change in urban agglomeration in the future and shows the mode of expanding from the existing construction land to the periphery.
“The Master Plan of Beijing (2016–2035)” requires the total scale of the city’s construction land (impervious surface, including urban and rural construction land, special land, external transportation land and some water conservancy facilities) will be controlled about 3670 square kilometers by 2035. The area of impervious surface under cropland protection scenario (
Figure 4d) meets the requirements, nevertheless, there is still a certain gap with the centralized construction area planned in the future, such as the northernmost areas around Beijing Daxing International Airport which should be developed and constructed. Comparing the three scenarios, the baseline scenario has the most severe urban expansion and has more negative impact on NPP; cropland protection scenario is the only scenario in which cropland is not transformed into impervious surface in a large area, but all kinds of land basically maintain the current situation, lacking the space for urbanization development; the ecological protection scenario has good protection for forest, wetland and water body, but there is a situation that a number of cropland is turned into impervious surface. Therefore, the land use planning of urban agglomeration should comprehensively consider the scenarios of ecological protection and cropland protection, which can not only ensure regional ecological security, but also improve the quality of cultivated land and protect food security. The change of land use in the process of urbanization in Beijing is representative. The land use transfer in Beijing is similar to that in Europe from 1950 to 1990: the proportion of forest and semi-natural areas increased slightly; artificial surfaces and agricultural areas changed greatly, in which the proportion of artificial surfaces increased and the proportion of agricultural land decreased [
53]. The results suggested different processes are taking place in different kinds of land use: the mountains northwest of Beijing are dominated by forest management; intensification and urbanization are mainly encountered on the plain. However, the international community has increasingly recognized the importance of maintaining “sustainable” ecosystems to protect the environment on which we depend. The researchers explored the methods and tools of integrated landscape management for nature conservation, physical/territorial planning, watershed management, land arrangement projecting and forestry planning [
54,
55].
4.3. Effect on Vegetation Net Primary Productivity (NPP)
On the one hand, the change of land use from one type to another is often accompanied by a large amount of carbon exchange. For example, when forests with high biomass are converted into farmland, grassland or cities with low biomass, large amounts of CO
2 will be released into the atmosphere which may cause a decrease in NPP of vegetation. The expansion of global croplands, pastures, plantations, and urban areas in recent decades generated considerable losses of biodiversity and also potentially undermined the capacity of ecosystems to sustain food production [
56]. in the process of industrialization in Beijing, a large amount of land is being changed into construction land, resulting in the increase of impermeable water surface. According to the result of hot spot analysis (
Figure 7), when
p < 0.01, the cold spots are mainly concentrated in the periphery of urban area and water area which may taking negative effects to NPP. On the other hand, in addition to natural factors, policy regulation and economic driving are also important causes of land use change and its spatial and temporal disparities. Typical examples of this are the abandonment of the former republics following the upheaval in Eastern Europe and the collapse of the Post-Soviet Union [
57]. With the continuing development of the city, urban planning priorities have gradually changed, the urban greening intensity has increased, and the vegetation condition has steadily improved [
58]. It can be seen from
Table 5 that the main land types in the hot spot of vegetation NPP are forest and grassland which are mainly distributed in the northwest of Beijing. What is more, the transformation of land use types in hot spot mainly occurs in the transformation from grassland to forest about 21.816 km
2. This is also a partial confirmation of the gradual improvement of vegetation cover in China, which may play a role in relieving the two main problems in Beijing: soil erosion and air pollution.
The results of this study (
Figure 4 and
Figure 5) are similar to those of Peng, J.’s study [
59]: from 2001 to 2009, at first, with the expansion of urban areas, ecological land was gradually occupied which led to a decrease in NPP, and finally the NPP increases occurred in highly developed urban zones, which depended to some extent on the growth of green land, local eco-environmental management and urban planning. Therefore, NPP in Beijing showed an obvious upward trend with a series of ecological forestry projects from 2010 to 2020. As Beijing has been highly developed urban zones, the future land use will not change greatly in the next 10 years and the promotion of NPP will exist which is consistent with the predicted results (
Figure 6b). In addition, continuous decline areas of the future development of NPP belong to the development area in this study and continuous rise areas account for 84.76%.
However, unlike Beijing, land cover and land use changed in some areas have reduced vegetation coverage and net ecosystem production [
60,
61]. The reason may be the local inaction to the forest which resulting in the decline of its area under the action of human activities. Therefore, the simulation of future development can provide a new basis for local planning, especially in similar countries and regions in the process of urbanization.
In 2019, Nature [
62] released research reports pointing out that China alone accounts for 25% of the global net increase in leaf area with only 6.6% of global vegetated area and China is engineering programs to conserve and expand forests with the goal of mitigating land degradation, air pollution and climate change. Although the area of cold spot of NPP changes in Beijing is large (
Figure 7), it has more forest cover and the government attaches importance to the protection of ecological environment. The overall NPP has maintained a stable rising level and will continue to rise (
Figure 6).In the process of urbanization, the protection of forests and other natural resources in Beijing made the proportion of vegetation coverage increase, and the vegetation NPP also showed an upward trend, which has a certain reference significance for the future urban planning of developing countries. For example, in the development process of some cities, the proportion of vegetation and net ecosystem production decreased [
60,
61]. Beijing, which has a relatively rapid urbanization process, can provide important information for land use planning and sustainable urban development in similar urban expansion areas, especially in less developed countries. Enoguanbhor, E.C. and others observed mismatches between past/current land cover and the existing land use plan [
61]. The mismatch was also between Beijing’s regional land use plan and unregulated urban expansion (“The Master Plan of Beijing (2004–2020)” requires that the scale of construction land in 2020 be controlled at 1650 square kilometers, but the actual area is 3475.76 square kilometers). Therefore, it is more necessary to carry out multi scenario future land use simulation to provide a scientific basis for urban planning. This paper can provide a way for cities in China and around the world to carry out spatial planning for sustainable development.
4.4. Limitations and Future Work
At present, some achievements have been made in the research of NPP estimation model, but there are a few studies on NPP prediction. Lixia, W. [
22] coupled CASA and CA-Markov model, finding that comparing the estimate and predict values of NPP in 2015, the kappa coefficient reaches 0.8776 which indicates that the coupled model has high accuracy and good applicability for NPP prediction. This study also attempted to use the coupled model (CASA and PLUS model) to predict the values of NPP. NPP was divided into 5 types, 7 types and 10 types as land use types, and the kappa coefficients are 0.584571, 0.524487 and 0.508822, respectively, which only achieved the level of moderate consistency. In the next step, we will try to improve the accuracy of the coupling model or study a better model to predict the value of NPP. Moreover, the influencing factors of NPP are relatively complex, such as the combination of water and heat, the physiological and ecological characteristics of vegetation, and there are also interactions among various climate factors. Therefore, it is required in the following study to take multiple driving factors into account predicting spatiotemporal variations of NPP.
Our future work plan will also appropriately expand the spatial scale of the research. The research will not only be limited to the better developed Beijing area, but also include the areas with large differences in development, such as Hebei Province and Tianjin city, China.