Abstract
The Manas River Basin is located in the inland arid area of China. It has a unique natural environment that contains a mountain, oasis, and desert complex ecosystem. Changes in land use type have had significant impacts on the social, economic, and ecological environment in the basin. Based on the remote sensing interpretation data of land use types from 1980 to 2020 in the Manas River Basin, using ArcGIS 10.2 and Fragstats 4.2 and other software to study the temporal and spatial evolution of land use, landscape pattern, and ecological service value (ESV) in the Manas River Basin, several key results were obtained. (1) Unused land accounted for the largest proportion of the total area at about 44%, and the smallest proportion was construction land at 1%, the construction land and farmland areas increased significantly to 82.16 and 34.87%, while the woodland and grassland area decreased to 15.06 and 14.34%, respectively. (2) Between 1980 and 2020, the inflows and outflows of the quantitative transfer tracks for farmland, grassland, and unused land were highly dominant, but the frequent conversion among various types of land led to the transfer tracks becoming more diversified. (3) From 1980 to 2020 the complexity and fragmentation of landscape in the basin decreased, and the heterogeneity, differences, and connectivity of the landscape increased. (4) The ESV of the Manas River Basin had a tendency to initially decrease and then increase, which increased from 237.27 × 108 yuan in 1980 to 238.10 × 108 yuan in 2020. The above research results can not only provide a basis for the ecological improvement of the Manas River Basin but also provide a reference for the study of other basins/regions in arid areas.
1 Introduction
Land use/cover change (LUCC) has been a hot issue in the study of global ecological environment change for a long time [1,2]. It has major impacts on the hydrological process [3], the carbon effect [4], ecological service value (ESV) [5], and the environment [6], and also promotes changes in regional, watershed, and global ecosystems [7]. Furthermore, changes in human activities, the social economy, and the natural environment determine the development direction, trend, and the degree of LUCC. Therefore, LUCC studies play an important role in understanding the changes in landscape pattern and ESV.
Researchers have extensively investigated the changes in landscape pattern and ESV under land use evolution. A study of the impact of rapid development and urbanization on the landscape pattern of the Tabriz metropolitan area from 1996 to 2016 showed that most natural land areas, such as grasslands, were converted into bare and urban land, with LUCC resulting in increased fragmentation and reduced aggregation of the landscape pattern [8]. A landscape index is the method most commonly used to study the changes in landscape pattern characteristics [9]. Changes in the landscape pattern of Sancaktepe Municipal District on the Asian side of Istanbul Metropolitan City, Turkey, were analyzed using landscape metrics, and the results showed that the mean patch size increased, while the total edges and the number of patches decreased between 2002 and 2009 [10]. After using the mathematical model and landscape index evaluation method, a study showed that the landscape pattern of the Shanxi mountainous area is a zigzag and fragmented under LUCC [11]. Studies of the mechanism driving spatiotemporal farmland changes in a Karst gully in Guizhou Province showed that the comprehensive effect of nature, economy, and policy led to significant spatiotemporal change and diversified the development of farmland function in the study area [12]. An analysis of landscape grade and landscape scale in Fengqiu County found that as human influence increases, the land use intensity increases, but the landscape heterogeneity decreases [13]. Therefore, research on the evolution of landscape patterns under land use change includes the dynamic spatiotemporal evolution process, the characteristics of the landscape pattern [14,15], the change characteristics of the landscape pattern at different scales [16,17], and the driving factors and mechanisms leading to landscape pattern change [18,19]. The evolution of land use and landscape ecological pattern will inevitably affect the ecological distribution characteristics, structural composition, and the development process, all of which change the ESV [20]. From 1998 to 2011, Crespin and Simonetti estimated the ESV in El Salvador, it was found that the dynamic change in LUCC reduced the natural landscape area by 12%, resulting in an annual loss of ESV of 2.6% in the study area [21]. Some researchers have estimated the value of global ecological services and found that the annual loss of ecological services caused by LUCC from 1997 to 2011 was about US$4.3 to US$20.2 trillion [22]. Researchers calculated ESV for Shijiazhuang from 1998 to 2018, and evaluated the ESV under a future land use scenario based on the CA–Markov model [23]. Another research group analyzed the driving factors affecting ESV under land use change in the main urban area of Guangzhou, they concluded that population and gross domestic product are the dominant factors driving ESV change [24]. The spatial change in ESV in Weiku oasis was evaluated and the value-added area was found to be decreasing year by year from 1994 to 2016, with the value-added area and impairment area showing a decreasing trend. Therefore, in recent years, research on the value evaluation of ecological services and its driving factors has become more extensive [25].
The Manas River Basin is the largest basin in the Northern Piedmont of Tianshan Mountain. The basin is located in an arid area, with perennial drought and little rain. Large-scale water and soil development has caused water shortages, groundwater levels have changed, and natural vegetation has declined in the Manas River Basin. In addition, due to the large-scale development of agriculture and water-saving irrigation technology in Xinjiang, large areas of natural land have been reclaimed for production, and land use has undergone significant changes, the natural environment of the river basin has been destroyed, and the ESV has decreased significantly. Water resources play an important role in changes in the underlying surface. Compared with the water-rich zone, the underlying surface of the Manas River Basin has a simple landscape structure and poor ecological stability. The basin is jointly managed by the local government and the Xinjiang Construction Corps, and the impact of human activities is significant, resulting in more complex and frequent changes in the landscape pattern. Over the past 40 years, studies of land use change and the landscape pattern in Manas River Basin have found that the large-scale transformation of natural land into production and living land has reduced the dominance of the natural landscape and increased the degree of fragmentation [26]. The process and trend for land use change in the watershed were quantitatively analyzed using a geo-information spectrum analysis, with the results showing that the process of land use change was stable, but the farmland area was continuously expanding [27]. Some scholars have found that population inflow and reclamation of saline alkali land are the two main driving forces for the change in basin landscape pattern [28].
Researchers worldwide have made important advances in land use research, such as determining the evolution of land use, the evolution of landscape patterns caused by LUCC, and the evaluation of ecological effects. These studies have a certain reference value for the rational development and utilization of regional land resources, protection of the natural environment, and regional sustainable development. However, there is a lack of research on the impact of land use changes on the landscape and ESV in a mountain oasis desert complex ecosystem (MODS) in arid areas. The Manas River Basin is a typical arid area with distinct natural environmental characteristics, namely, the MODS. In addition, as the main irrigated and economically developed area in Xinjiang, with its large-scale promotion of water-saving irrigation technology and rapid urbanization, the natural oasis of the Manas River Basin has gradually been transformed into an artificial oasis and great changes have taken place in land use. Previous studies of the Manas River Basin mainly focused on a quantitative analysis of land use and changes in ESVs over time, with a lack of research on land use and ESV changes at the spatial scale. Therefore, based on the remote sensing data for land use in the Manas River Basin from 1980 to2020, this study analyzed the quantitative and spatial migration trajectory for land use in the basin using a Chord diagram and a gravity center migration model [29]. The study also assessed the changes in the landscape pattern in the river basin, and conducted a quantitative analysis of the ESV of the Manas River Basin and the changes in their spatial distribution. The research results provide an important basis for the sustainable development of arid areas, such as rational planning of land use in basin, construction of landscape patterns, and the protection of ecological security.
2 Materials and methods
2.1 Study area survey
The Manas River Basin is located in the hinterland of Eurasia, a typical arid area in northwest China. The basin is located on the northern foot of Tianshan Mountain and the southern margin of the Junggar Basin, Xinjiang, with geographic coordinates of about 43°27′–45°21′N, 85°01′–86°32′E [30] (Figure 1). The river basin is divided into ten cities and counties, such as the eighth division of Bingtuan, Shihezi City, Manas County, Shawan County, and Bulsaik Mongolian Autonomous County [31]. The river basin area is about 3.40 × 104 km2 and there are 6 rivers in the river basin, including Manas River, Bayingou River, and Jingou River, Ningjia river, Taxi river and et al. The Manas River having the largest and longest flow in the basin, originates from the melt water of Tianshan Mountain, and finally flows into the Manas Lake [32]. The Manas River Basin is located in the inland arid area. Its climate is characterized by drought, low rainfall, and high evaporation intensity. The annual average temperature is about 5.9℃, the average annual precipitation is 100–200 mm, and the average annual evaporation is 1,500–2,100 mm [26]. The altitude and ecological belt distribution divides the basin into a plain desert area, a plain oasis area, and a southern mountainous area in a north to south direction.
An overview of Manas River Basin.
2.2 Data sources and processing
Land use data for the Manas River Basin from 1980 to 2020 were obtained from the 1:100,000 land use topographic map provided by the Resource and Environmental Science and Data Center of Chinese Academy of Sciences (https://www.resdc.cn/), three Landsat-TM remote sensing images (1980, 1990, and 2010), one Landsat TM/ETM remote sensing image (2000), and two Landsat-8OLI remote sensing image (2015 and 2020) of the Manas River Basin. The images selected for analysis and the spatial resolution was 30 m × 30 m. The ENVI 5.3 software was used to apply a quadratic polynomial and nearest pixel method was used for geometric correction of three scene images, including a spatial position transformation and pixel gray value recalculation to meet the accuracy requirements. The Radiometric Calibration tool was used to calibrate the image and convert the digital number value to the reflectance at the sensor. The FLASH tool was used to perform an atmospheric correction on the radiometric image and eliminate the influence of factors such as the atmosphere and illumination on the reflection of ground objects. The preprocessed remote sensing image was cropped, and the multi-spectral remote sensing image of the study area was cropped according to the required geographic vector boundary. To determine the current land use classification of the Manas River Basin, reference was made to the land use classification system used by the Resource and Environment Science and Data Center of the Chinese Academy of Sciences (GB/T21010-2017). The human–computer interaction visual interpretation method was used to interpret the land uses into six land types: farmland, woodland, grassland, water area, construction land, and unused land. Based on the random verification points obtained from field verification and Google Earth high-resolution images, the classification results were tested by the confusion matrix method. The results showed that the classification accuracy was greater than 85%, indicating that the interpretation results would meet the research needs. The social and economic data were from the Construction Corps Statistical Yearbook, the Xinjiang Statistical Yearbook, and the China Grain Yearbook.
2.3 Research methods
2.3.1 Dynamic change in land use
2.3.1.1 Analysis of the change in land use degree
Previous research results were used to determine the parameters for land use degree in the study area [33] (Table 1). The Zhuang and Liu research method for the determination of land use comprehensive degree was used to calculate and analyze the dynamic change in land use [34]. The formula for the comprehensive land use index (L) is as follows:
where L is the comprehensive land use index in the study area; n is the number of land use types; A i is the area of land use type i, hm2; P i is the parameter of land use degree i; and A T is total area of study area, hm2.
Land use degree parameters for different land use types
| Types of land use | Farmland | Woodland | Grassland | Water area | Construction land | Unused land |
|---|---|---|---|---|---|---|
| Parameters of land use degree (p i ) | 0.165 | 0.114 | 0.215 | 0.12 | 0.936 | 0.063 |
2.3.1.2 Analysis of land use dynamic change
The change trends for the different land use types during the study period can be analyzed using the dynamic degree of land use, and the comprehensive dynamic degree of land use (S) method was used to analyze the change trend for the overall structure of land use types in different time periods [35]. The formula is as follows:
where A it is the area of land use type i at the beginning of the study, hm2; UA i is the area of class i land use in the study period, hm2; t 1 and t 2 represent the beginning and the end of the study, respectively; and n is the number of land use types.
2.3.1.3 Quantitative change trajectory model of land use
The land use transfer matrix is the application of the Markov model to land and can quantitatively and qualitatively analyze land use [36]. The land use transfer matrix is as follows:
where A ij refers to the area of class i land transformed into class j land in a certain period of time.
A Chord diagram is mainly used to show the complex relationship and correlation between multiple research objects, whereas a visualization analysis is widely used in informatics and biological research. The start and end flow data record the flow of moving objects in space and time, using graph theory; the total amount of data is defined as G = (V, T), where V is the set of all spatial regions and T is the set of time periods under time granularity division, and when v n ∈ V, t n ∈ T, n is the granularity of space-time division, the rows represent the starting position or time, and the columns represent the end position or time, there are n × n possibilities and they form a two-dimensional matrix, with each matrix element corresponding to the statistics of flow direction [37]. To clearly show the changes in the quantity and direction of land use types in the study area, the Markov model was used to construct a two-dimensional matrix of excavated land transfer, which can be transformed into a Chord diagram for a better visual effect. A quantitative trajectory model of land use in Manas River Basin was then established.
2.3.1.4 Trajectory model of land use spatial change
A gravity center migration model of land use types can clearly show the migration trajectory of the spatial distribution of land use types over a certain period of time. The calculation formulas for the gravity center coordinates are as follows [29]:
where X and Y represent the coordinates of the gravity center for each region over a certain period of time; Cti is the ith patch area of a certain land type in the study area, i is the total number of patches of this land type; and Xi and Yi represent the coordinates of the center of gravity of the ith patch in a certain region.
2.3.2 Landscape pattern research methods
Research on the change characteristics of a landscape pattern plays an important role in regional landscape structure and ecological security. Landscape indexes are one of the main methods used to study the change in landscape pattern. There is a certain relationship among the indexes, but their significances vary. ArcGIS 10.2 was used to convert the vector map of the study area to one with an accuracy of 30 m × 30 m after spatial analysis. Then, the grid data are converted to a TIFF format and the landscape index is calculated using the landscape pattern analysis software Fragstats 4.2, which uses origin 2018 to map the landscape index. Combined with actual characteristics of the basin, this study selected indexes from the two levels of type and landscape according to the aggregation and dispersion of patches and landscapes, dominance, connectivity, shape complexity, and diversity [38]. The landscape index includes the landscape shape index (LSI), the patch cohesion index (COHESION), the edge density (ED), the contagion index (CONTAG), the modified Simpson’s diversity index (MSIEI), the largest patch index (LPI), Shannon’s diversity index (SHDI), and the aggregation index (AI). Its ecological significance is shown in Table 2.
Landscape pattern index and its ecological significance
| Landscape pattern index | Ecological significance |
|---|---|
| LSI | Represents the regularity and dispersion of patches and landscapes, the larger the value, the greater the complexity of patch or landscape. |
| COHESION | The connection degree of landscape types within a given distance threshold. |
| ED | The greater the value, the higher the degree of fragmentation. |
| CONTAG | It indicates the extensibility and aggregation of landscape, reflects the connectivity of patches, 0 < connect ≤ 100. |
| MSIEI | Reflects the uniformity and superiority of landscape. |
| LPI | It Represents the proportion of the largest patch, which can reflect the dominant landscape type in the region, 0 < LPI ≤ 100. |
| SHDI | The larger the value, the smaller the difference of landscape area, SHDI ≥ 0. |
| AI | It indicates the aggregation degree of landscape. |
2.3.3 Research on ESV
2.3.3.1 Calculation of the ESV
Without considering the price fluctuation factors, the average grain price for Xinjiang in 2015 was 2.08 yuan/kg according to the unit price of crops. Under the condition of no labor input, the economic value of ecology under the natural conditions of the study area is 1/7 of the economic value of the grain yield per unit area of farmland. Combining this value with the following formula allows the economic value of production per unit area of farmland ecosystem in Manas River Basin to be calculated as [39]
where E a is the economic value of production provided by a farmland ecosystem per unit area, yuan/hm2; n represents the number of crop species; i is the type of crop; m i is the planting area of crops, hm2; p i is the national average unit price of the crop, yuan/kg; q i is the yield per unit area of such crops, kg/hm2; and M represents the total area of crop cultivation, hm2.
Xie et al. applied the research method used by Costanza to obtain the value of global ecological services [39,40]. They studied and formulated the equivalent value of ecosystem in China based on the actual situation. The equivalent value was modified after referring to the “Ecosystem services value unit area of Chinese terrestrial ecosystem” and the “Ecosystem service equivalent value per unit area” used by previous Chinese researchers [39,41] and the actual situation in the Manas River Basin. Therefore, woodland corresponds to forest; the grassland equivalent factor is the average value for grassland, shrub, and meadow; and water area includes water bodies and wetland, and therefore its equivalent factor was taken as the average value of the two land types. Construction land includes aesthetic landscape value, but not other ESVs, which meant that its equivalent factor is set to 0, which unused land took the average value for desert and bare land. The economic value of the natural grain output of farmland in the study area is calculated to be about 1121.29 yuan/hm2, and the value equivalents of different land use ecological services in the Manas River basin are formulated (Table 3).
ESV equivalents of land use types in the Manas River Basin (yuan (hm2·a)–1)
| First class types | Second class types | Farmland | Woodland | Grassland | Water area | Construction land | Unused land |
|---|---|---|---|---|---|---|---|
| Supply services | Food production | 650.35 | 112.13 | 257.90 | 224.26 | 0.00 | 11.21 |
| Raw material production | 100.92 | 2915.37 | 381.24 | 44.85 | 0.00 | 16.82 | |
| Regulatory services | Gas conditioning | 1244.64 | 3924.53 | 1356.77 | 1009.17 | 0.00 | 11.21 |
| Climate regulation | 571.86 | 3027.50 | 3576.93 | 9844.97 | 0.00 | 78.49 | |
| Water conservation | 672.78 | 3588.14 | 897.04 | 20116.02 | 0.00 | 33.64 | |
| Waste disposal | 1838.92 | 1468.90 | 1468.90 | 20385.13 | 0.00 | 11.21 | |
| Support services | Soil formation and protection | 11.21 | 4373.05 | 1513.75 | 964.31 | 0.00 | 22.43 |
| Biodiversity | 235.47 | 3655.42 | 1502.53 | 2803.24 | 0.00 | 381.24 | |
| Cultural services | Aesthetic landscape | 100.92 | 1435.26 | 661.56 | 5550.41 | 11.21 | 11.21 |
| Total | 5427.07 | 24500.29 | 11616.61 | 60942.36 | 11.21 | 577.47 |
The ESV of Manas River Basin from 1980 to 2020 is calculated as follows [42]:
where ESV is the ESV of land use type, yuan; A i is the area of this kind of land, hm2; and V i is the equivalent value of ESV, yuan/hm2.
2.3.3.2 Calculation of the ecological contribution rate
Based on the calculations for the ecological contribution rates of different land use types in the Manas River Basin from 1980 to 2020, the dominant and sensitive factors for ESV change can be calculated using the following formula [40]:
where S KT is the contribution rate for ecological services, %; and ΔESVKT is the change in the ESV of class K land in T period, yuan.
2.3.3.3 Sensitivity analysis of ESV
The results of the assessed ESV had to be tested. Many economics researchers have used the elasticity coefficient to calculate the sensitivity index and test the calculated ESV to determine the degree of dependence of the ESV on the ESV coefficient [43]. This study used the coefficient of sensitivity (CS) to test the accuracy of the ESV results. The ESV coefficient of different land use types in Manas River Basin was adjusted (±) 50% to calculate the change in the total ESV in the basin. If CS > 1, the ESV was elastic to the value coefficient of ecological services. If CS < 1, the ESV lacked elasticity, indicating that the ESV coefficient was suitable for the study area. The greater the CS value, the more critical the accuracy of the value coefficient. The formula for the calculation of CS is as follows [44]:
where CS represents the coefficient of sensitivity; ESV i and ESV j represent the total value of ecological services before and after adjustment, respectively, yuan; VC ik and VC jk , respectively represent the value coefficient of class k land ecological services before and after adjustment; and K indicates land use type.
3 Results and analysis
3.1 Analysis of different land use type changes
3.1.1 Characteristics of and changes in land use structure
From 1980 to 2020, the main types of land use in Manas were farmland, woodland, grassland, water area, construction land, and unused land. As shown in Figure 2, the northern part of the basin is mainly composed of unused land, while the central part is mainly composed of farmland, grassland, water area, and construction land. Among them, the distribution of the water area is scattered and shows a point distribution, the farmland and grassland are distributed in flakes, while the construction land is relatively concentrated and patchy. The south mainly contains unused land, woodland, and water area, among which the woodland distribution is continuous and strip-shaped, whereas the water area is affected by the mountainous terrain, shows a branch distribution, and flows from south to north, it includes potential water resources, such as glaciers and bare rocks. The northern part of the basin is mainly desert area consisting of sandy land, Gobi, and saline alkali land. The central region is an oasis plain area that contains farmland, grassland, reservoirs, rivers, urban and rural areas, and industrial and mining land types.
Land use map of the Manas River Basin from 1980 to 2020: (a) 1980, (b) 1990, (c) 2000, (d) 2010, (e) 2015, and (f) 2020.
All types of land use areas in the Manas River Basin changed in quantity (Table 4 and Figure 3) between 1980 and 2020, but the change amplitude was different. Among the land use types in the basin, unused land was the largest, accounting for 44.91–42.69% of the total area of the basin, followed by grassland, farmland, water area, woodland, and construction land, accounting for 33.13–28.38, 22.98–16.99, 3.08–2.54, 1.61–1.34, and 1.59–0.85%, respectively. Over the past 40 years, the area of unused land in the basin has been the largest type of land use, accounting for about 40% of the basin area, but the area displayed a slow decreasing trend year by year from 1980 to 2020 (4.94%). Grassland and unused land displayed the same change trend, but the area decreased significantly in the study period to 14.34% of the original area. The proportion of woodland decreased to 15.06%, but from 1980 to 2020, the area of farmland increased significantly annually and was 34.87% more than the original amount; by 2020 the water area had increased by 20.97%, construction land accounted for only about 1% of the basin, but it displayed a continuously increasing trend.
Area of land use types in the Manas River Basin from 1980 to 2020/(km2)
| Land use type | ||||||
|---|---|---|---|---|---|---|
| Year | Farmland | Woodland | Grassland | Water area | Construction land | Unused land |
| 1980 | 5786.59 | 536.29 | 11281.16 | 867.08 | 288.43 | 15291.96 |
| 1990 | 5919.35 | 551.09 | 11271.38 | 907.11 | 365.42 | 15037.16 |
| 2000 | 6557.07 | 473.64 | 10601.43 | 916.78 | 410.77 | 15091.80 |
| 2010 | 7328.37 | 460.77 | 10162.20 | 933.06 | 444.59 | 14722.51 |
| 2015 | 7824.69 | 455.52 | 9668.53 | 913.31 | 525.58 | 14663.87 |
| 2020 | 7804.49 | 455.52 | 9663.77 | 1048.93 | 542.70 | 14536.10 |
Land use and its change characteristics in the study area from 1980 to 2020.
3.1.2 Overall structure change for different land use types
It can be seen from Figure 4 that the comprehensive land use index (L) displayed an increasing trend from 1980 to 2020. In 1980, L had its lowest value of 14.03%, after 1990, the value of L in the basin rose to reach a maximum value of 14.59% in 2020, the results showed that the development of mechanization and the application of science to agricultural technology increased the land use degree. The comprehensive land use dynamic (S) of the Manas River Basin displayed a decreasing fluctuation trend during the study period. From 1980 to 1990, S reached a maximum of 31.15%, indicating that human activities played a significant role in land function change. The value of S declined from 1990 to 2000, indicating that the impact of human activities on land type change had weakened. From 2000 to 2020, the fluctuation of S decreased, and from 2015 to 2020, the value of S reached a minimum of 3.13%, indicating that during this period human activities had the least effect on the change in land function, this was probably due to the introduction of relevant ecological protection policies in this period.
Dynamic change in land use in the study area from 1980 to 2020.
3.2 Temporal and spatial changes in land use
3.2.1 Transfer track for land use quantity
As shown in Figure 5, the change track for land use quantity in the Manas River Basin from 1980 to 1990 shows that other land use types changed most obviously to grassland, and it was farmland and unused land that mainly flowed to grassland. The outflow behavior for farmland is significant, and mainly flows into unused land and grassland, the inflow and outflow of unused land are obvious, and were mainly mutual inflows and outflows with grassland. The transformation trajectory of land use types showed that the transformation of land use types in this period was relatively stable. From 1990 to 2000, the conversion behavior of farmland was more obvious, mainly showing the inflow of grassland and unused land, and the outflow of farmland to grassland and construction land, the transformation of construction land occurred more frequently in this period. Overall, compared to the previous period, the transformation among different regions was more frequent and diversified, which increased the uniformity of transformation among different regions. From 2000 to 2010, the transformation of land use types was mainly manifested in the transformation from other land use to farmland, among which grassland and unused land were the largest. Compared to the previous period, the track line of this period is relatively sparse and thin, which indicates that all types of land in this period remained relatively stable, the activity of land use transformation declined, and the area of various types of land transfer decreased. From 2010 to 2015, the land use transformation characteristics are similar to those in the previous period, they mainly reflect the transformation of unused land and grassland into farmland, the transfer amount decreased, but the outflow of farmland increased, mainly into grassland and construction land. The transition track for land use in this period is relatively thick, indicating that the transfer amount between different land types slightly increased. From 2015 to 2020, the land use transformation in the study area was in a stable state, there was no conversion of woodland, the transfer track lines between other types of land were relatively sparse, and the conversion frequency between land types was low, the outflow of unused land to water area was the most obvious change.
Magnitude of the transfer of land use in the Manas River Basin from 1980 to 2020. (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2015, (e) 2015–2020, and (f) 1980–2020. Note: The trace lines of different colors indicate the flow direction among different land use types over the period, the different fan-shaped areas indicate the area of each land use type, and the track line represents the conversion between different land types. The thicker the line is, the greater the conversion amount is.
In general, the land use types in the Manas River Basin frequently changed between 1980 and 2020, and the transformation trajectory showed both diversity and richness. The inflow and outflow of farmland and grassland were relatively high, and the transformation area was large. Farmland was mainly transformed into grassland and construction land, and the inflow was mainly land transformed from grassland and unused land. In addition, the outflows of grassland and unused land were more significant, grassland was mainly converted into farmland and unused land, and unused land was mainly converted into farmland and grassland. In summary, the mutual transformation of farmland, grassland, and unused land was the most obvious and the mutual transformation area was large. Over the past 40 years, the farmland area has significantly increased, while the grassland and unused land area has significantly decreased. Although the transformation of other types of land was diverse, the transfer area was small. After 40 years of temporal and spatial changes in land use, the change in the sizes of the different areas were unused land > grassland > farmland > water area > woodland > construction land to unused land > grassland > farmland > water area > construction land > woodland.
3.2.2 Track of land use spatial transfer
As can be seen from Figure 6, the gravity centers of different land use types are scattered across different parts of the study area, which indicates that the distribution of various land types in the basin is uneven. In addition, the gradient change is significant from 1980 to 2020. In general, the migration direction of the gravity centers for different land use types was mainly north–south, which is closely related to the cascade distribution of the ecological belt in the study area. The migration range of the gravity centers for the main land types from large to small is grassland > woodland > farmland > water area > construction land > unused land. This indicated that under the influence of human activities and the social economy, the ecological belt in the basin has undergone different degrees of evolution.
Trajectory of gravity center migration in the Manas River Basin from 1980 to 2020. Note: ■1980, ●1990, □2000, ○2010, ▲2015, and *2020.
Figures 6 and 7 show the migration trajectory of the gravity centers of land use types in the Manas River Basin from 1980 to 2020. From 1980 to 1990, the gravity center for farmland moved to the southwest and then to the northeast between 1990 and 2000. After 2000, the gravity center for farmland moved to the northwest, indicating that the farmland area in the oasis region decreased in the early 1980s. The farmland area increased in the central and northern parts of the oasis area due to the large-scale reclamation of grassland. The center of gravity of woodland, grassland, and construction land moved to the southwest, with the migration path of the grassland gravity center following an inverted “Z” shape, and its gravity center shifted direction to be the opposite to that of farmland. The gravity center migration range of construction land was the smallest, and the gravity center migration trajectory was “S” type. The center of gravity of the water area and unused land gradually shifted to the northeast during the study period. There was an extensive agricultural development in the oasis area and the increase in the area of river channels was the main reason for the northward migration of the water area center of gravity. From 2015 to 2020, due to the increase in the area of Manas Lake, the center of gravity of the water area moved to the northeast. The displacement of the gravity center of unused land was small after 1990, with its center of gravity shifting slightly to the east, indicating that the degree of unused land development and utilization gradually decreased. The center of the gravity migration trajectory of different land use types was consistent with the development of the basin.
Migration track of the land use center of gravity in Manas River Basin from 1980 to 2020. (a) Farmland. (b) Woodland. (c) Grassland. (d) Water area. (e) Construction land. (f) Unused land.
3.3 Landscape pattern change characteristics
It can be seen from Figure 8 that from the perspective of landscape types, the landscape indexes of different land use types in the study area have different trends. From 1980 to 2020, the LSI for farmland increased the most, reaching a maximum value of 27.18 in 2015. The landscape index of woodland and grassland displayed a trend of declining fluctuations, with the minimum values being 13.63 and 22.11, respectively. The LSIs for unused land, water area, and construction land were relatively small, but they displayed an upward trend year by year. From 1980 to 2020, the patch cohesion values of other land use types were all greater than 99.3 except for construction land, which indicated that the cohesion degree of different land use types in the basin was high. Furthermore, the patch cohesion degree for construction land increased significantly by 0.85, which is related to socio-economic development in the basin. It can also be seen from the change in ED that after years of reclamation and urbanization, the edge densities for farmland, unused land, and construction land increased by 0.001, 0.19, and 0.17, respectively. This shows that there were more broken patches, but the densities of the other land types and their broken patches decreased.
Changes in landscape pattern across the Manas River Basin from 1980 to 2020. (a) LSI, (b) COHESION, (c) ED, (d) CONTAG, (e) LPI, and (f) MSIEI.
Figure 8 also shows that the landscape structure of the basin significantly changed after 40 years of development. The CONTAG and the modified Simpson’s index show the opposite trend. The value of the CONTAG was in the range of 1–100 and smaller the value, the smaller the patches within the landscape. From 1980 to 2020, the CONTAG displayed a trend of first decreasing and then increasing, it decreased from 1980 to 2015 and increased to a maximum of 62.95 in 2020. After 2015, the degree of fragmentation in the Manas River Basin decreased and the connectivity increased. The modified Simpson’s index dropped from 0.643 in 1980 to 0.640 in 2020, displaying a trend of first rising and then decreasing, this showed that the distribution of different landscape patches in the watershed was relatively even, and the differences among the various landscapes increased slightly. The LPI in the study area displayed a decreasing trend year by year, from 44.91 in 1980 to 43.06 in 2020. This showed that the distribution of the dominant landscape types decreased and the intensity of human interference increased. The overall LSI displayed a trend of first increasing and then decreasing. From 1980 to 1995, with the development of agriculture, the patch shape became simple and the LSI decreased. After 1995, the LSI increased year by year, reaching a maximum of 22.82 in 2015, this showed that the shape of the landscape was highly complex, the degree of patch separation was large and displayed an increasing trend, from 2015 to 2020, the LSI reduced by 3.6 due to the strengthening of ecological protection, there was a reduction in the area of land used for agricultural production, the area of natural land increased, and the development of patches was simplified. From 1980 to 2015, the SHDI for the Manas Basin displayed an increasing trend and reached a maximum value of 1.37 in 2015, this shows that the difference among landscape areas in the basin decreased over time. The SHDI decreased by 0.08 from 2015 to 2020, indicating that the heterogeneity, diversity, and complexity of the landscape decreased. The AI displayed a trend of rising volatility, in 2015, the landscape AI decreased to its minimum value of 99.32, indicating that the landscape aggregation degree decreased, but the fragmentation degree and the degree of heterogeneity increased. From 2015 to 2020, the degree of agglomeration of the landscape increased substantially, the degree of fragmentation decreased. Overall, the landscape pattern structure of the Manas River Basin only changed slightly from 1980 to 2000 and was relatively stable. During the period of 2000 to 2020, the landscape structure changed significantly, indicating that it was in an active state.
3.4 Ecosystem service value
3.4.1 Changes in the ESV of land use in the Manas River Basin
Table 5 shows that from 1980 to 2020, the overall ESV of land use in the Manas River Basin displayed a trend of first decreasing and then increasing. The overall ESV increased by 0.83 × 108 yuan, a year-on-year increase of 0.36%. From 1980 to 1990, the value of land use ecological services increased by 3.26 × 108 yuan, an increase of 1.38%, but there was a large decrease of 5.60 × 108 yuan from 1990 to 2000, a year-on-year decrease of 2.33%. From 2000 to 2010, the value of ecological services decreased by 0.19%, whereas from 2010 to 2015, it decreased by 4.41% × 108 yuan, a decrease of 1.88%, from 2015 to 2020, the largest increase in the value of ecological services was 8.03 × 108 yuan. The ESVs of woodland and grassland significantly decreased, and the ESVs of farmland and construction land increased year by year during the study period.
Changes in the land use ESVs across the Manas River Basin from 1980 to 2020/× 108 yuan
| Land use type | |||||||
|---|---|---|---|---|---|---|---|
| Year | Farmland | Woodland | Grassland | Water area | Construction land | Unused land | Total |
| 1980 | 31.40 | 13.14 | 131.05 | 52.84 | 0.00 | 8.83 | 237.27 |
| 1990 | 32.12 | 13.50 | 130.94 | 55.28 | 0.00 | 8.68 | 240.53 |
| 2000 | 35.59 | 11.60 | 123.15 | 55.87 | 0.00 | 8.72 | 234.93 |
| 2010 | 39.77 | 11.29 | 118.05 | 56.86 | 0.00 | 8.50 | 234.48 |
| 2015 | 42.47 | 11.16 | 112.32 | 55.66 | 0.01 | 8.47 | 230.07 |
| 2020 | 42.36 | 11.16 | 112.26 | 63.92 | 0.01 | 8.39 | 238.10 |
3.4.2 Ecological service function value of the Manas River Basin
It can be seen from Figure 9 that the gas conditioning, waste disposal, water conservation, and biodiversity service values are the main components and determinants of the basin ESV. Over the past 40 years, the overall ESV of the Manas River Basin displayed a trend of first decreasing and then increasing, the ESV increased from 237.27 × 108 yuan in 1980 to 238.10 × 108 yuan in 2020. The ESV of food production, water conservation, and waste disposal increased significantly by 12.9, 9.59, and 10.72%, year-on-year, while the ESV of raw material production, soil formation and protection, and biodiversity significantly decreased by 9.68, 12.68, and 7.11%, respectively. The ecosystem service function of the Manas River Basin could be divided into four primary ecosystem service functions and 11 secondary ecosystem service functions. Based on the value of each function, the regulation service value of the primary ecosystem service function is the largest, followed by support service, supply service, and cultural service. The secondary ecological service function values are climate regulation, waste disposal, water conservation, biodiversity, gas conditioning, soil formation and protection, provision of an aesthetic landscape, food production, and raw materials production.
Ecosystem service values for the Manas River Basin from 1980 to 2020.
To analyze the spatial change characteristics of the ESV of the Manas River Basin from 1980 to 2020, a 2 km × 2 km square grid was taken as the research unit, a space-time distribution map of the ESVs in the study area was constructed (Figure 10), and the natural breakpoint method was used to divide it into five levels from low to high. It can be concluded from Figure 10 that areas with a high ESV were mainly distributed in the southern part of the mountainous and oasis plain areas. These areas had high altitudes and were close to the Tianshan Mountains, the annual rainfall was large and the amount of ice and snow melt was also large, resulting in a large water area, the woodland and grassland coverage was relatively high, humans and economic activity have had little impact on the region. The ESV gradually decreased from the middle of the oasis plain area to the desert area, because the central part of the basin is a flat plain with abundant water resources, good lighting conditions, and a concentrated population, the extensive agricultural and economic development has gradually reduced the value of ecological services. Areas with a low ESV were mainly distributed in the desert area in the northern part of the basin. Because this area is mainly desert, it is dry and rainless all year round, and vegetation is not fully developed. In terms of a time series, from 1980 to 2015 there has been a decline in the area with a high ESV, and the area with a low value has gradually increased. From 2015 to 2020, the area with a high ESV has increased.
Spatial distribution of ESVs in Manas River Basin. (a) 1980, (b) 1990, (c) 2000, (d) 2010, (e) 2015, and (f) 2020.
3.4.3 Sensitivity analysis of the ESV
The CS can verify the result calculated by the ESV coefficient of the study area, and judge whether the calculated result conforms to the actual situation of the study area. It can be seen from Figure 11 that from 1980 to 2020, grassland had the highest CS value (0.47–0.55), it displayed a decreasing trend year by year, indicating that grassland changes had a large impact on the ESV of the Manas River Basin. The lowest CS was found for construction land, indicating that changes in its coefficient value had little effect on the ESV. The CS of woodland and unused land displayed a decreasing trend year by year, indicating that the two land use types decreased the total ESV in the Manas River Basin. The CS of both farmland and the water area increased by about 0.46, indicating that both had an amplifying effect on the total value of ecological services in the Manas River Basin. The CS of all land use types in the Manas River Basin from 1980 to 2020 was less than 1, indicating that the ESV of the basin was not flexible to the value of the ESV coefficient used for the Manas River Basin in this study. The ESV coefficient adopted was in line with the actual situation of the Manas River Basin, and the result of the calculation was credible.
Coefficient of sensitivity of ESV.
3.4.4 Contributions rate of land use type ESV change in Manas River Basin from 1980 to 2020
As can be seen from Table 6, from 1980 to 2020, the proportional contribution made by grassland ecosystem services to the overall change in ESVs in the Manas River Basin was the largest at 43.45%, while the contribution made by construction land ecosystem services was the smallest at 0.01%. From 1980 to 2020, the proportional contributions made by farmland and the water area in the basin were also relatively large, with values for farmland between 1990 and 2000, 2000 and 2010, and 2010 and 2015 were 25.15, 38.73, and 27.50%, respectively. From 1980 to 2020, the grassland, farmland, and water area made the largest contributions to the ecological services, with a total contribution rate of 94.41%, this indicated that grassland and farmland had the most dominant and sensitive effects on the change in ESV across the Manas River Basin.
Contributions of ecosystem service value of different land use types in the Manas River Basin from 1980 to 2020/%
| Land use type | ||||||
|---|---|---|---|---|---|---|
| Year | Farmland | Woodland | Grassland | Water area | Construction land | Unused land |
| 1980–1990 | 19.04 | 9.58 | 3.00 | 64.47 | 0.02 | 3.89 |
| 1990–2000 | 25.15 | 13.79 | 56.55 | 4.29 | 0.00 | 0.23 |
| 2000–2010 | 38.73 | 2.92 | 47.21 | 9.17 | 0.00 | 1.97 |
| 2010–2015 | 27.50 | 1.31 | 58.55 | 12.29 | 0.01 | 0.35 |
| 2015–2020 | 1.29 | 0.00 | 0.65 | 97.19 | 0.00 | 0.87 |
| 1980–2020 | 25.33 | 4.58 | 43.45 | 25.63 | 0.01 | 1.01 |
4 Discussion
The land use change in the Manas River Basin was significant and were closely related to the implementation of long-term national policies, the rapid development of the social economy, and the substantial increase in population. Since the 1950s, there has been a large amount of wasteland reclamation in the oasis plain area, the area of grassland, water area, woodland, and unused land has been greatly reduced, the agricultural land and production and living land has increased sharply, and the natural oasis has gradually begun to transform into an artificial oasis. After the 1980s, under the background of the household contract system, and reform and opening up, the policy of contracted output and contracted responsibility to each household was gradually implemented, and the land management mode changed to centralized and decentralized management. At the same time, the development of water-saving irrigation technology has meant that water use efficiency in the basin has greatly improved, and the farmland reclamation rate in the plain area has accelerated [27,45]. After 2000, China put forward the ninth 5-year plan and the policy of western development. The policies of “Separation of three powers” and “Exemption of agricultural tax” were rapidly carried out in the river basin, which greatly promoted the transformation of land use function and significantly changed the land use types [46]. In 2017, the state proposed to control the three control lines of the ecological protection red line, permanent basic farmland, and the urban development boundary, and land use began to enter a phase of intensive development.
From 1980 to 2015, land use change research in the Manas River Basin mainly focused on the quantitative change process and characteristics, and the land use transfer matrix based on the Markov model was used for quantitative analysis. The results showed that the rapid expansion of farmland was mainly due to the reclamation of wasteland and natural grassland, although there were frequent transformations of other land use types, the transfer area was small [47]. To date, there have been few studies on the visualization of land use change [48]. In this study, a Chord diagram was used to visualize the relationship between land use change in the Manas River Basin, and its flow, the flow direction, and the diversity of land use change in a specific period were also identified. The flow of farmland was a large, two-way flow, the flow of grassland and unused land was small and mainly a single flow type, and the flow of other types of land was small and a two-way flow, which indicated that the development of the agricultural economy is gradually active. Research on the spatiotemporal change trajectory of different land use types is limited and has mainly focused on the analysis of gravity center shifts in the oasis area. The results show that the center of gravities for woodland, grassland, and construction land moved to the southwest, the center of gravities for the water area and unused land moved to the northeast, and the center of gravity for farmland moved to the northwest. The results also show that farmland reclamation mainly took place in the northern part of the oasis plain, resulting in a large expansion of farmland to the north, which caused the center of gravity for farmland to shift to the northwest. Furthermore, the decrease in grassland area in the northern part of the oasis area and the increase in grassland area in the south have meant that the center of gravity for grassland has shifted southward. The center of gravity for construction land has shifted to the southwest, indicating that the population and industrial scale in the southwest part of the oasis plain area has increased. Land use change in the Manas River Basin has had a significant impact on the landscape pattern. Previous studies that used Fragstats software, the landscape index, and other methods have shown that the landscape pattern change in the Manas River Basin was diverse, fragmented, and complex [26,49]. The main drivers of landscape pattern change in the watershed are human activities, among which the rapid growth of population and large-scale grassland reclamation are the most obvious [28]. Before 1995, due to the transformation of grassland and unused land into farmland, the area of farmland expanded and connected with other land areas, this has meant that the patches in the basin have become aggregated and the aggregation degree has increased. However, the differences among the different landscape types decreased and the degree of landscape evenness increased. From 1995 to 2015, the rapid increase in areas under irrigation caused an ecological water shortage, at the same time, over the past 40 years, people have carried out large-scale felling and have overgrazed the land in the basin, resulting in large-scale reductions in the woodland, grassland, and water areas across the basin. These processes have increased landscape fragmentation, and have led to poor connectivity and a clear increase in heterogeneity. After 2015, with the control of ecological protection red line, the landscape pattern has been simplified and the degree of aggregation has increased.
In recent years, there have been many evaluations of ecological services in typical areas in Xinjiang, the ESV of the study area displayed a fluctuating and increasing trend, which was similar to that of other regions in Xinjiang, but there were also differences. From 1993 to 2019, the total ESV in Yuli County increased by 32.69 × 108 yuan, with a trend to first decrease and then increase [50], and the ESV of the Bosten Lake Basin and Tarim River Basin both had a trend of increasing fluctuations during the study period, increasing by 8.53 and 7.10%, respectively [51,52]. The ESV of the Ebinur Lake Basin in Xinjiang decreased by approximately 85.863 × 108 yuan from 1996 to 2016, displaying a continuous decreasing trend year by year [53], the ESV trend in the Ulungu River Basin was the opposite of that of the Ebinur Lake Basin, and the rate of increase decreased over time [54], the trend of ESV of Manas River Basin and Ebinur Lake Basin is the same, and it has decreased significantly over the years [55]. Researchers have used the unit area equivalent factor method to evaluate the ESV from 1990 to 2015 and found that the ESV of the Manas River Basin displayed a downward trend [56]. It can be seen that the research results differed in different research periods, but the ESV tended to display the same trend in the same research period, which verified the accuracy of the research results in this study. Due to regional differences, as well as differences in the driving factors and assessment methods, there were differences in the ESV in various regions, but in most of Xinjiang, the ESV displayed a trend of increasing volatility. After 2015, various regions have paid increasing attention to ecological protection and the natural environment has improved, the ESV in various regions has gradually increased or the rate of decline has decreased, the ecological development of the Manas River Basin was consistent with this observation.
In this study, using remote sensing land use data from 1980 to 2020 combined with geographical information software, based on previous quantitative analysis of land use transformation and using a Chord diagram and center of gravity migration trajectory, the spatial changes in land use in the Manas River Basin were evaluated, this enabled the dynamic changes and temporal and spatial characteristics of land use in the study area to be determined. Previous studies have shown that the use of spatial statistics and their analysis to study the temporal and spatial distribution of ESVs is obviously insufficient, and this study has advanced the methods used to evaluate the ESVs. The Manas River Basin is a typical inland arid area, the large-scale development of water-saving irrigation technology over time has enabled the transformation from a natural to artificial oasis, which makes the area suitable for the study of ESV under a MODS system in an arid area. This study also has some shortcomings. In previous studies researchers have used 30 m resolution remote sensing images to study the landscape pattern of the Manas River Basin [26,28,32], the same resolution was used to study and analyze the landscape pattern of the watershed in recent years. This can intuitively show the changes in the basin landscape pattern, but a different 57], further research and analysis should therefore be conducted using the landscape index under different resolutions. This study revised the ESV equivalent of the study area according to the actual situation in the Manas River Basin to evaluate the ESV of the study area, this method is widely used, and has the characteristics of a strong operability, simplicity, and intuition, although the calculation results are rough. The ESV coefficient of the Manas River Basin needs to be further revised and improved according to the payment capacity and willingness of local people, this would ensure that the research results are more accurate and in line with the actual situation of the basin. At the same time, the driving forces and influencing factors of the changes in ESV in the Manas River Basin could be further studied and analyzed using mathematical statistics.
5 Conclusion
Taking the Manas River Basin as the research area, this study analyzed the impact of LUCC on the landscape pattern and ESV changes under the MODS system in an arid region. The results can be used to ensure the optimal allocation of land resources in the basin. The main conclusions were as follows:
In the past 40 years, unused land, grassland, farmland, and construction land are mainly concentrated in desert and oasis plain areas in the basin. The water area is mainly distributed in the southern mountainous area and the plain area, but its distribution is relatively scattered, woodland is distributed in the northern part of the southern mountainous area. From 1980 to 2020, the area of construction land and farmland increased most significantly by 81.26 and 34.87%, while the area of woodland and grassland decreased by 15.06 and 14.34%, respectively. During the study period, the land use degree significantly increased. In addition, the effects of human activity on land use change increased at first, but then decreased.
From 1980 to 2020, there have been frequent mutual transfers of land use types between various regions. Among them, the outflow of grassland and unused land and the inflow of farmland were most significant. Due to the combined effects of ecological belts and the development of human society, the center of gravity of land use types has changed significantly. The centers of gravity for woodland, grassland, and construction land shifted to the southwest, the centers of gravity for water area and unused land shifted to the northeast, and the center of gravity for farmland shifted to the northwest.
From 1980 to 2020, the modified Simpson’s index and Shannon diversity index both showed a trend of first increasing and then decreasing. Over the past 40 years, the LPI and LSI values decreased by 1.85 and 1.76%, respectively. This shows that the heterogeneity of the landscape in the basin increased, the differences in the landscape have increased, and the landscape has developed simplistically. The increase in the fluctuation of the CONTAG and the landscape aggregation indicates that the degree of fragmentation in the basin has reduced, and the connectivity of the landscape has been enhanced.
From 1980 to 2020, the overall ESV of land use in the Manas River Basin displayed a trend of first decreasing and then increasing, and its overall ESV increased by 0.83 × 108 yuan. Over the past 40 years, the ESV of the Manas River Basin has also displayed a trend to first decrease and then increase, its ESV increased from 237.27 × 108 yuan in 1980 to 238.10 × 108 yuan in 2020. In terms of space, the value of ecological services gradually decreased from south to north.
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Funding information: This research was funded by the third scientific expedition project in Xinjiang (Grant No. 2021xjkk0804), Xinjiang Production and Construction Corps scientific and technological break through project (Grant No. 2021AB021), International cooperation and exchange project of Xinjiang production and Construction Corps (Grant No. 2022BC001) and the National Natural Science Foundation of China (Grant Nos. U1803244, 51969027) and Shihezi University High-level Talent Scientific Research Initiation Project (RCZK202026).
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Author contributions: Conceptualization: Y.D., X.H., and X.L.; methodology: Y.D., X.H., and X.L.; software: Y.D. and X.L.; analysis: Y.D., X.L.I., and W.L.; investigation: X.G., Y.W., and W.L.; resources: G.Y.; data curation: X.L. and X.H.; preparation of original draft: Y.D. and X.L.; cartography: Y.D., Y.W., and X.L.I.; editing and revisions: X.H., G.Y., and J.Q.; project administration: X.H.; funding acquisition: X.H. All authors have read and agreed to the publication of this manuscript.
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Conflict of interest: The authors declare no conflict of interest.
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