Temporal–Spatial Synergistic Restructuring of Eco-Economic Value in Xinjiang Oasis from Multi-Objective Optimization Perspective

Abstract

To address the challenges of ecological degradation and economic imbalance in arid zone development, this study took the oasis region of Xinjiang as the research object. A multi-objective optimization model was constructed based on the ecosystem service value (ESV) and economic value (ECV), and the NSGA-III was employed to optimize the land use structure under water resource constraints. The findings indicate the following: (1) from 1990 to 2020, economic benefits increased fivefold, whereas the ecosystem service value declined by 6.7%, showing a clear divergence; (2) the overall regional coordination deteriorated, with economic expansion significantly encroaching upon ecological space in certain areas; (3) under the optimization scenario, the balanced development strategy increased economic benefits by 12.3%, enhanced the ecological value by 8.6%, and improved coordination by 15.4%, demonstrating that optimizing land allocation can synergistically enhance both economic and ecological benefits while ensuring the rational use of water resources and ecological security. This study not only reveals the squeezing effect of economic expansion on ecological functions but also provides scientific decision-making support for the sustainable development of arid oasis regions under resource constraints, holding significant theoretical and practical implications.

1. Introduction

With rapid economic growth and increasing pressure on resources and the environment, regional development now faces the dual challenges of ecological degradation and economic imbalance [1,2]. This issue is particularly critical in arid regions such as Xinjiang, where limited water resources and fragile ecosystems mean that economic expansion often comes at the expense of environmental quality [3]. Such dynamics have led to a gradual decline in the ecosystem service value (ESV), thereby affecting the long-term development and ecological security of the region [4]. In recent years, rapid urbanization and agricultural modernization have dramatically changed land use patterns [5]. While these structural transformations have boosted economic efficiency, they have also accelerated the loss of ecosystem services, resulting in a pronounced “deviation” between economic growth and ecological functions [6].

In light of these challenges, how to achieve the synergistic progress of economic development and ecological protection has become an important issue to be solved. To this end, this study took the Xinjiang oasis as the research object, constructed a dual-indicator evaluation system integrating the economic value (ECV) and ecosystem service value (ESV), and explored the path of optimizing the regional land use structure by using the multi-objective programming (MOP) model and NSGA-III under water resource and ecological security constraints. The aim was to answer the following three key questions: (1) How can the spatial and temporal evolution characteristics of the economic value (ECV) and ecosystem service value (ESV) of different land use types in the Xinjiang oasis be revealed? (2) What are the intrinsic value transfer and interaction mechanisms between economic benefits and ecological service functions in the process of land use type conversion? (3) Under water resource and ecological security constraints, how can a multi-objective programming (MOP) model be constructed to optimize the regional land use structure so as to achieve the synergistic reconstruction and enhancement of the ecological value and economic value?

Traditionally, regional economic development has been measured mainly by GDP indicators, but this approach does not fully reflect regional sustainability [7]. In order to compensate for this shortcoming, scholars have proposed the concept of “ecological and economic value reconstruction”, which suggests that the services provided by ecosystems, such as water resource regulation and climate regulation, should be quantified at the same time as the evaluation of economic growth [8]. Studies have constructed a valuation system based on the ecosystem service value (ESV), revealing the intrinsic link between ecological services and economic activities [9]. However, most of the current studies mainly focus on static evaluation or single-indicator analyses and pay insufficient attention to the dynamic mechanism of ecological function restoration in the process of land use conversion [7]. While the rapid advancement of urbanization and agricultural modernization has enhanced economic efficiency, it has also exacerbated the loss of ecosystem services [5]. In arid regions such as Xinjiang, economic growth often comes at the expense of the ecosystem due to water scarcity and fragile ecosystems [3]. This situation has led to a gradual decline in the ESV in the region and adversely affected long-term development and ecological security [4]. Currently, there is still an obvious research gap as to how to restore ecological functions through “value reconstruction” in arid regions such as Xinjiang [10]. Therefore, it is of great theoretical and practical significance to establish a comprehensive evaluation framework that can dynamically capture the interaction between ecological services and economic values in land use change [11].

Regarding the value of ecosystem services in Xinjiang, some studies have shown that the ESV in the region showed an increasing and then decreasing trend between 1980 and 2020 [7]. Some studies have pointed out that grasslands and water bodies contribute more than 70% to the ESV, but the reduction in water and forest areas in recent years has significantly weakened ecological functions [7]. In the Yanqi Basin, some scholars found that the expansion of wetland and cultivated land contributed to the increase in the ESV [12]; meanwhile, the continuous decline of grassland and forested area significantly weakened the ecological regulation function [9]. In addition, some studies have shown that due to rapid economic development, the coordination level between socio-economic systems and oasis ecosystems in northern border towns is low, with only some towns having a coordination index of about 0.46 [13]. In order to solve the problem of the economic and ecological imbalance in the region, some studies have begun to apply the multi-objective planning (MOP) model, which helps to optimize the regional land use structure under the integrated consideration of the total land area and water resource constraints [14]. Compared with traditional spatial simulation methods, such as FLUS or SD-FLUS, the multi-objective planning model demonstrates higher flexibility [15,16]. However, the current discussion on the use of MOP models for dynamic ecological and economic reconstruction is still insufficient [17]. Therefore, this study used the MOP model and NSGA-III to construct a dynamic evaluation framework under water resource and ecological security constraints with a view to achieving the optimization of the regional land use structure and the synergistic development of the ecological economy [18].

2. Materials and Methods

2.1. Study Area

The study area was Xinjiang, located in northwestern China, with a total area of 1.66 million square kilometers (Figure 1). The region is located in the hinterland of the Eurasian continent, with a typical temperate continental arid climate, extremely scarce water resources, and a relatively fragile ecological environment. In recent years, along with the rapid expansion of the artificial oasis and the rapid development of the regional economy, the land use pattern has changed significantly, and the contradiction between the ecology and economy has become more and more prominent, providing a complex background for the sustainable development of the region [19].

2.2. Data Sources

The data used in this study to calculate the ESV included land use and statistical data. The land use data were obtained from the Centre for Resource and Environmental Science and Data, Chinese Academy of Sciences. (https://www.resdc.cn/ accessed on 3 June 2024), with a resolution of 30 m. Statistical data on agriculture, forestry, animal husbandry and fisheries, and grain production and planted areas are mainly from the Xinjiang Statistical Yearbook (1991, 2001, 2011, and 2021) (https://tjj.xinjiang.gov.cn/ accessed on 3 December 2024). Water resource data and precipitation data are from the Xinjiang Water Resources Bulletin (2001, 2011, and 2021) (http://slt.xinjiang.gov.cn/ accessed on 3 December 2024).

2.3. Accounting for Ecosystem Service Value and Economic Value

2.3.1. Accounting for Ecosystem Service Value

In this paper, based on the modified ecosystem service value equivalent per unit area by Xie Gao Di et al. [20,21,22], all types of land use in the study area were multiplied with their corresponding unit value coefficients and accumulated to obtain the ESV (

Table 1. Accounting coefficients for ecosystem service value and economic value (CNY/hm²).

Service Types	Items	Agricultural Land (AL)	Forest Land (FL)	Grassland (GL)	Water Body (WB)	Built-Up Land (BL)	Unused Land (UL)
Provisioning Services (PSs)	Food Production (FP)	1535.25	439.54	419.56	851.24	0.00	0.00
	Raw Material Production (RMP)	791.79	10,006.43	611.78	244.73	0.00	0.00
	Water Resource Supply (WRS)	−1605.28	519.30	340.72	14,692.84	−273.00	0.00
Regulating Services (RSs)	Gas Regulation (GR)	1326.88	6633.58	2166.07	819.32	541.52	21.28
	Climate Regulation (CR)	494.78	9904.06	5720.36	4042.00	1430.09	0.00
	Environmental Purification (EP)	143.65	2920.94	1886.64	5905.48	471.66	106.40
	Hydrological Regulation (HR)	1590.76	6699.42	4190.60	28822.27	0.00	31.92
Supporting Services (SSs)	Soil Preservation (SP)	553.31	4027.26	2637.73	989.57	659.43	21.28
	Maintenance of Nutrient Cycling (MNC)	164.93	307.61	202.83	74.48	13.45	0.00
	Biodiversity (BD)	180.89	3671.29	2394.24	2713.33	65.54	21.28
Cultural Services (CSs)	Aesthetic Landscape (AEL)	79.80	1610.07	1058.11	2011.06	10,411.40	10.64
ESV		5256.75	46,739.50	21,628.65	61,166.31	13,320.09	212.81
ECV		11,988.25	10,190.52	2131.09	0.00	316,563.51	406.44

). It was specifically expressed as follows:

$$ESV=\sum _{k=1}^n{A}_k·V{C}_k,$$

(1)

where $A_k$ is the area of the land use category (hm²), and $V{C}_k$ is the unit service value of the land use category (CNY/(hm²)).

2.3.2. Economic Calculation of Value (ECV)

Due to the different price levels in different periods, the GDP was deflated and adjusted in order to eliminate the effect of inflation [23]. Taking 1990 prices as the benchmark, the deflator for 1990 was set to be 1. The GDP of all the other years was converted to the 1990 price level by dividing it by the corresponding deflator (Pt), as follows:

$$GD{P}_{adj}\left(t\right)={\displaystyle \frac{GDP\left(t\right)}{P_t}}$$

(2)

where GDP(t) is the raw GDP value in year t, and Pt is the deflator in year t (1990). For each region, we multiplied the unit economic value (Yj) (CNY/(km²-year)) of each land use type with its optimized area and accumulated the values to obtain the regional economic benefits:

$$ECV=\sum _{k=1}^n{A}_k·Y_k.$$

(3)

where Y_k is adjusted to 1990 price levels.

2.4. Value Transfer Matrix

In order to portray the mutual transformation of different land types and the increase or decrease in their economic and ecological values in time, a value transfer matrix was constructed [24]. Its mathematical model expression is shown in Equation (4):

$$S_{ij}=[\begin{array}{cccc}{S}_{11}& S_{12}& \dots & S_{1n}\\ S_{21}& S_{22}& \dots & S_{2n}\\ \dots & \dots & \dots & \dots \\ S_{n1}& S_{n2}& \dots & S_{nn}\end{array}]$$

(4)

where Sij represents the land area of land type i transformed into land type j, and n represents the number of land use types. Types i and j represent the land use types at the beginning and end of the transfer.

Combining the economic value per unit (ECV) and the ecological value per unit (ESV) for each type and calculating the corresponding increase or decrease in the value during the transformation process can be written as follows:

$$\Delta V_{ij}=\left(V_j-V_i\right)\times S_{ij}$$

(5)

where $S_{ij}$ is the area converted from type to type, and $V_{\mathrm{j}}$ and $V_i$ are the unit values of the types (GDP or ESV). Aggregating all transformations gives the positive and negative value flow statuses. The value transfer matrix is useful for assessing the positive and negative economic and ecological impacts of anthropogenic land use change.

2.5. Coordination Index Calculation and Grading

In order to quantify the coordination between economic and ecological benefits in the study area at different times, the economic–ecological harmony degree (EEHD) was defined [25]. Using the growth rate ratio method to compare the growth rates of the ESV and ECV, it can be expressed as follows:

$${\mathrm{ESVP}}_{\mathrm{pr}}={\displaystyle \frac{{\mathrm{ESV}}_{T_2}-{\mathrm{ESV}}_{T_1}}{{\mathrm{ESV}}_{T_1}}}$$

(6)

$${\mathrm{ECVP}}_{\mathrm{pr}}={\displaystyle \frac{{\mathrm{E}\mathrm{C}\mathrm{V}}_{T_2}-{\mathrm{E}\mathrm{C}\mathrm{V}}_{T_1}}{{\mathrm{E}\mathrm{C}\mathrm{V}}_{T_1}}}$$

(7)

$$\mathrm{EEHD}={\displaystyle \frac{{\mathrm{ESVP}}_{\mathrm{pr}}}{{\mathrm{ECVP}}_{\mathrm{pr}}}}$$

(8)

When the ratio is >0 and the value is large, it means that the ecological growth rate is higher relative to the economic growth rate; if the ratio is <0, it means that there is a conflict between the two. The detailed grading is shown in

Table 2. Classification of the ecology–economy harmony degree.

EEHD	Harmony Degree
<−1	High conflict
−1~−0.5	Moderate conflict
−0.5–0	Low-intensity conflict
0~0.5	Low harmony
0.5~1	Moderate harmony
≥1	High harmony

.

2.6. Multi-Objective Planning (MOP) Model Construction and Solution

2.6.1. Objective Function Construction

Under the constraints of regional water resources, ecological security, and other constraints, the optimal land use structure that synergizes economic and ecological benefits was sought so as to achieve the reconstruction of the ecological and economic values [26]. This paper defines three optimization objectives, including economic benefits, ecological benefits, and coordination objectives:

(1)

Economic benefit objective function

In order to maximize the economic benefits in the region, the objective function was defined as follows:

$$\mathrm{m}\mathrm{a}\mathrm{x}{E}_d\left(x\right)=\sum _{i=1}^n{d}_i·x_i$$

(9)

where $x_i$ denotes the area of the category i land after planning (unit: hm²). $d_i$ is the unit economic value of the category i land (CNY/hm²), which is obtained by the aforementioned ECV accounting;

(2)

Ecological benefit objective function

In order to maximize the ecological benefits in the region, the objective function was defined as follows:

$$\mathrm{m}\mathrm{a}\mathrm{x}{E}_p\left(x\right)=\sum _{i=1}^n{p}_i·x_i$$

(10)

where $p_i$ is the unit ecological value (CNY/km²) of the land in category 1, which is obtained from the aforementioned ESV accounting;

(3)

Ecological and economic synergy index objective function

In order to measure the coordinated development level between the economic benefits and ecological benefits, we defined the ecological and economic synergy index (coordination index, CI) as follows:

$$\mathrm{m}\mathrm{a}\mathrm{x}{C}_{\mathrm{new}}(\mathrm{x})=1-{\displaystyle \frac{\left|E_d-E_p\right|}{E_d+E_p}},$$

(11)

where $E_d$ is the global economic benefit, and $E_p$ is the global ecological benefit. When the two are more balanced, the closer to 1, and the larger the gap, the smaller the value.

2.6.2. Constraints

(1)

Water Resource Constraints

For each region (i), the total water consumption does not exceed the total regional water resources:

$$\sum _{j=1}^5{w}_{ij}{x}_{ij}\le W_i$$

(12)

where $w_{ij}$ is the unit water consumption (m³/(km²-year)) of land type j in region i;

(2)

Ecological water constraints

The water consumption of ecological land (woodland, grassland, waters) in each region is required to be at least a proportion of the total water resources of the region ($R_{eco}$) by setting different proportions of ecological water use: 0.5 in the case of ecological priority, 0.4 in the case of balanced development, and 0.3 in the case of economic priority:

$$\sum _{j\in \{2,3,4\}}{w}_{ij}{x}_{ij}\ge R_{eco}\times W_i$$

(13)

(3)

Lower ecological area constraint

The optimized ecological land area is not less than 50% of the current ecological land area:

$$\sum _{j\in \{2,3,4\}}{x}_{ij}\ge 0.5\times \left(\sum _{j\in \{2,3,4\}}{A}_{ij}\right)$$

(14)

2.6.3. NSGA-III Optimization

In order to solve the above multi-objective planning problem, the NSGA-III (Non-dominated Sorting Genetic Algorithm III) was used in this study, and its basic process is as follows [27]:

(1)

Population initialization

The initial population is randomly generated within the upper and lower bounds of the given decision variables. Let the decision variable vector be X = [x11,…, x15, x21,…, xN5];

(2)

Non-dominated sorting

For all individuals in the population, the population is divided into fronts by non-dominated sorting based on the value of the objective function. Definition: for any two individuals, i and j, i is said to non-dominate j if for all objectives fk(i) ≤ fk(j) and there exists at least one objective (k) such that fk(i) < fk(j);

(3)

Crossover and Variation

The crossover and mutation operators are used to generate offspring and combine them with the non-dominated ordering of the parents to select the next generation of the population. Crossover usually uses simulated binary crossover (SBX), and mutation uses polynomial mutation;

(4)

Multi-objective crowding distance/reference point distribution

The NSGA-III maintains the solution diversity by presetting reference points (or segmentation lines) to ensure an even distribution of Pareto frontiers;

(5)

Iterative termination

The algorithm iterates until the maximum number of generations or when the convergence condition is satisfied, retaining the final non-dominated frontier solutions as the Pareto optimal solution set.

3. Results

3.1. Comprehensive Evaluation of Land Values in Oasis Areas

From 1990 to 2020, the value of the ESV declined slightly from CNY 546,973 million to CNY 510,110 million, with an overall decrease of about 6.7% (Figure 2a), while the value of the ECV increased significantly from CNY 68,545 million to CNY 433,988 million, with an increase of more than five times. During this period, the ESV and ECV showed a “divergent” trend: ecosystem service functions had limited growth or declined, while the economic value expanded rapidly, reflecting the potential contradiction and pressure between regional economic development and ecological protection.

Among the sub-services (Figure 2b), Food Production increased from CNY 17.357 billion to CNY 21.430 billion, and Aesthetic Landscape also increased slightly, suggesting that the supply and cultural functions have been strengthened to a certain extent; however, the Water Resource Supply and Climate Regulation also increased slightly. However, key functions such as the Water Resource Supply (WRS) and Climate Regulation (CR) have all declined significantly, especially the Water Resource Supply, which has dropped by about 50%, highlighting the impacts of water scarcity, climate change, and vegetation degradation. Overall, there has been a general decline in regulatory and supportive functions, and it is necessary to strengthen the protection of ecological services such as water conservation, biodiversity, and environmental purification in the course of economic development.

3.2. Analysis of Land Value Transfer in Oasis

During the period from 1990 to 2000 (Figure 3a), cropland received a positive inflow, gaining CNY 6.536 billion from grassland and CNY 10.17 billion from built-up land, while woodland showed a negative outflow, transferring CNY 2.27 billion to cropland and CNY −3.488 billion from grassland. Grassland as a whole shows an outflow, with its value transfer to bare land as high as CNY −19.963 billion, while bare land received CNY 11.94 billion from grassland, showing that there was a strong positive value compensation for bare land in this period. The internal transfers from watersheds and built-up land were relatively small, but watersheds still had a negative outflow of CNY −1.14 million.

The overall transfer trend was amplified in the time periods of 2000–2010 and 2010–2020 (Figure 3b,c). In 2000–2010, cropland received CNY 33.66 billion from built-up land, while the positive inflow of bare land was even higher at CNY 95.51 billion; meanwhile, both forest land and grassland showed relatively large negative transfers of CNY −20.61 billion and CNY −20.26 billion, respectively, indicating that the ecological function land was greatly squeezed in the economic development. From 2010 to 2020, there was a large positive inflow of grassland (CNY 17.62 billion), and there was also a flow of nearly CNY 100 billion to construction land. Aggregate value transfers from 1990 to 2020 (Figure 3d) show that arable land overall gained a positive inflow of CNY 355.79 billion, while forest land and grassland suffered large value losses. In the process of long-term land use change, the economic value of arable land and construction land has been increasing with economic development and urbanization expansion, while ecological land has faced a loss of value, reflecting the contradiction between the regional economy and ecological protection.

3.3. Evaluation of Coordination Between Ecological Environment and Economic Development

From the overall trend (

Table 3. Ecological and economic harmonization of Xinjiang prefectures.

Administrative District	1990–2000	2000–2010	2010–2020	1990–2020
Urumqi	0.0142	0.0615	−0.0225	0.0094
Karamay	−0.0093	0.0018	−0.0048	−0.0019
Turpan	−0.0377	0.323	0.0068	0.0593
Hami	0.0277	0.2533	0.0052	0.051
Changji	−0.1211	−0.2454	0.0777	−0.0224
Bozhou	0.1848	0.0757	0.0143	0.0293
Bazhou	−0.0747	−0.0365	−0.1827	−0.03
Aksu	−0.0625	−0.0888	−0.034	−0.031
Kexu	0.0871	−0.2261	0.0237	−0.026
Kashgar	0.1574	−0.0918	−0.0456	−0.0225
Hotan	1.7467	−0.797	−0.0067	−0.1502
Yili	−0.0125	−0.1022	−0.0162	−0.0265
Tacheng	0.0945	0.0677	−0.0092	0.0184
Altay	−0.1355	0.0864	0.0202	0.0195
All Region	−0.0325	−0.0391	−0.0055	−0.0126

), a few regions (e.g., Urumqi, Hami, Bozhou) showed small positive values during the period 1990–2000, and these regions had slightly insufficient ESV growth rates compared to the ECV growth rates but were still able to maintain a certain positive interaction with the economy. The Hotan region showed an outstanding performance during this period, with a high value of the co-ordination degree of 1.7467, which reflects that the ESV growth rate is more obvious relative to the economic growth rate. In 2000–2010, the economic growth in most regions was significantly faster than the ESV growth, resulting in negative or small positive values for the degree of coordination, such as the Bayin’guoleng Mongol Autonomous Prefecture and Aksu region, where the economy and ecology are in conflict. Turpan city, however, has a positive value of 0.3230, reflecting the fact that the ESV and the economic growth can still be kept in good synchronization. From 2010 to 2020, with the acceleration of economic development, the coordination degree of most regions was low or negative, indicating that the growth rate of the ESV lagged behind the economic growth rate, and Urumqi and Bazhou also had negative or insufficient ESV growth rates. Overall, from 1990 to 2020, the economic development of each region was remarkable, but the ESV growth relatively lagged behind, resulting in an overall decline in economic–ecological coordination.

In terms of spatial distribution, the high degree of coordination in Hotan from 1990 to 2000 may be due to the relatively low ESV level at that time and the limited change in the GDP during the same period, resulting in a relatively favorable ESV growth rate. In contrast, the Bayinguoleng Mongol Autonomous Prefecture and Aksu region both have negative values in several periods, suggesting that their economic growth is rapid, but their ESV growth is insufficient, and the conflict between the two is more prominent. Urumqi also shows negative values for 2010–2020, suggesting that rapid urbanization has not been accompanied by ecological growth. Overall, the spatial and temporal variations in the economic–ecological coordination are obvious, and the economic growth rate in most regions still far exceeds the growth rate of the ESV, which puts higher demands on the sustainable use of resources and ecological protection in the future. All regions need to combine water resource control and ecological restoration projects to promote economic and ecological construction in a balanced manner so as to improve the level of economic–ecological coordination.

3.4. Optimization Analysis of Land Structure Based on Multi-Objective Optimization (MOP) Model

The optimization results based on the NSGA-3 (Figure 4a–c) show that the coordination indexes show a certain regular distribution with the increasing economic and ecological benefits, while in the low-Ed and -EP areas, the C value is relatively low or relatively dispersed. This indicates that there is a clear trade-off between the economy and ecology, and the solution closer to the Pareto front means a better integrated performance in the three objectives.

From the data (

Table 4. ESVs, ECVs, and C values under the three different scenarios (unit: CNY billion).

Administrative District	Ecological Priority			Balanced Development			Economic Priority
	ESV	ECV	C	ESV	ECV	C	ESV	ECV	C
Urumqi	100.25	265.48	0.55	66.83	357.31	0.32	50.12	417.86	0.21
Karamay	68.45	90.67	0.86	51.94	124.8	0.59	38.95	145.6	0.42
Turpan	128.67	115.34	0.95	92.58	153.26	0.75	69.44	178.81	0.56
Hami	480.56	210.45	0.61	349.84	277.57	0.88	262.38	323.83	0.9
Changji	335.78	390.12	0.93	257.45	552.08	0.64	193.09	644.1	0.46
Bozhou	195.34	135.67	0.82	150	157.55	0.98	112.5	183.81	0.76
Bazhou	825.67	440.89	0.7	628.14	572.93	0.95	471.11	668.42	0.83
Aksu	755.12	510.34	0.81	588.58	635.75	0.96	441.44	741.71	0.75
Kexu	81.45	53.67	0.79	60.32	59.02	0.99	45.24	68.85	0.79
Kashgar	435.67	465.89	0.97	338.8	569.34	0.75	254.1	664.23	0.55
Hotan	445.34	185.23	0.59	343.82	204.83	0.75	257.87	239	0.96
Yili	285.78	425.56	0.8	217.19	531.86	0.58	162.89	620.51	0.42
Tacheng	435.12	470.45	0.96	340.86	578.94	0.74	255.64	675.43	0.55
Altay	710.45	245.67	0.51	541.62	281.08	0.68	406.22	327.92	0.89
All Region	5200.78	4000.56	0.87	4028	5056.33	0.89	3021	5899.05	0.68

), the ecological priority scenario improves the ecological service value (ESV) in most regions; for example, the ESV of Urumqi City increases from CNY 8.354 billion to CNY 10.025 billion, while its ECV decreases from CNY 29.776 billion to CNY 26.548 billion, resulting in an increase in the composite indicator (C) from 0.44 to 0.55, which indicates that under the premise of guaranteeing an ecological water share of more than 50%, the ecological function has been strengthened. The cities of Karamay, Turpan, and Aksu all show a similar trend: the ESV slightly increases or remains robust, while the ECV decreases or grows more slowly, ultimately resulting in a relative improvement in the C and highlighting the ecological function.

In contrast, the economic priority scenario significantly compresses the ESV (from CNY 8.354 billion to CNY 5.012 billion in Urumqi, and from CNY 6.492 billion to CNY 3.895 billion in Kelamayi), while the ECV significantly increases (from CNY 29.776 billion to CNY 41.786 billion in Urumqi, and from CNY 10.400 to 14.560 billion in Kelamayi), resulting in a significant C-value decrease, reflecting a greater sacrifice of ecological water shares and ecological benefits. The balanced development scenario is in between, but the overall ESV is lower than that of the ecological priority scenario.

4. Discussion

4.1. Divergence and Harmonization of Economic and Ecological Values

From 1990 to 2020, the Xinjiang region as a whole shows the trend of a significant increase in economic benefits and a slight decrease in the value of ecological services. The phenomenon of economic and ecological “deviation” is obvious, which is closely related to the large-scale expansion of the artificial oasis and urbanization in the region. The rapid increase in economic benefits mainly relies on the expansion of arable land and construction land, but this expansion inevitably compresses the ecological land, such as forest land, grassland, and water, resulting in the impairment of ecosystem services, which, in turn, leads to the decline in the overall coordination index of the region. This finding is basically consistent with the results of domestic studies on rapid economic development at the expense of ecological functions in arid zones, suggesting that the current regional development model in Xinjiang urgently needs to find a new balance between economic growth and ecological protection.

Compared to the eastern coastal areas of China, although they have experienced rapid urbanization, the degradation of ecological land has been slower than that in the western arid zone due to the relatively strict land use policies [17]. In contrast, about 80% of the counties in the southern border region showed an initial ecological–economic deterioration trend during 2000–2020, and the total ESV decreased by CNY 167.99 × 10⁸ [21], suggesting that economic development has a more significant impact on ecosystem service values. In addition, studies in the provinces along the Silk Road Economic Belt also show that the western region has had a greater intensity of resource development and a continuous decline in its ecological carrying capacity, making the overall economic–ecological coordination lower than that in the eastern region [28]. Together, these studies confirm the widespread phenomenon of ecological–economic “deviation” in Xinjiang and emphasize the necessity of building coordinated ecological–economic development.

4.2. Multi-Objective Trade-Off of Land Use Structure Optimization

The Pareto frontier solution obtained by the NSGA-III shows that there is a significant trade-off relationship among the different optimization schemes in the three objectives of economic benefits, ecological benefits, and the coordination index. Under the condition of strictly guaranteeing the ecological water share and the lower limit of ecological land area in the ecological priority scheme, the optimization scheme obviously increases the value of ecological services but, at the same time, sacrifices part of the economic benefits. This result is consistent with the study of Yang Yujin [29] in the lakeside area of Poyang Lake, indicating that the expansion of watersheds and forested land can effectively enhance the ESV under the ecological priority strategy. The economic priority scheme significantly enhances the economic output through the expansion of arable land and construction land, but the ecological land is compressed, the ecological service function declines, and the coordination index is low. Similar to Xinjiang, studies in the northern Xinjiang township region show that accelerated socio-economic growth tends to lead to a decline in oasis ecosystem coordination, with a negative correlation between economic and ecological benefits [13]. The balanced development program strikes a compromise between the two, maintaining high economic benefits while protecting ecosystem services to a certain extent, resulting in a medium level of the coordination index. This compromise strategy has also been validated in national-scale ecological and economic coordination studies, and although the overall economic–ecological coordination tends to improve, the western region still faces greater ecological pressure and needs to balance economic development and ecological protection according to local conditions [30].

4.3. Policy and Management Implications

Based on the simulation results and analysis presented in this study, we propose the following management recommendations: (1) Optimize the land use structure: while promoting rapid economic growth, the expansion ratios of cultivated and construction land should be strictly controlled. (2) Strengthen water resource management: regions should develop differentiated water use strategies based on their water resource endowments and actual water consumption, ensuring that the proportion of water allocated for ecological purposes meets the minimum requirements, thereby safeguarding regional ecological security [31]. (3) Implement ecological compensation mechanisms: during the process of adjusting the land use structure, ecological compensation measures should be introduced to support regions experiencing losses in their ecological service value, thereby promoting the synergistic development of the regional ecology and economy [32].

4.4. Limitations of the Model and Future Improvements

Although this study has achieved certain outcomes in constructing a multi-objective optimization model and its solution algorithms, several limitations remain: Land use data may exhibit inconsistencies across different time points and spatial resolutions, which could affect the precision of the model results. Future research could employ high-resolution remote sensing data or improve land classification methods to enhance the result stability. Moreover, the current study is based on static data; future studies should consider dynamic coupling and scenario simulations, integrating factors such as climate change, population growth, and policy adjustments, to provide more forward-looking decision support for regional planning.

5. Conclusions

This study explored the reconstruction of ecological–economic values and the pathways to coordinated development in the oasis areas of Xinjiang. Based on ESV accounting, the MOP model, and the NSGA-III, the analysis examined the impacts of land use structure adjustments on economic benefits, ecological benefits, and their coordination. The main conclusions are as follows:

(1)

There is a marked divergence between rapid regional economic growth and declining ecological value. Temporal data indicate that the ECV has substantially increased over the past decades, whereas the ESV has generally exhibited a downward trend or an insufficient growth rate. This reflects that economic development has encroached upon high-value ecological land, thereby weakening ecological functions;

(2)

The value flow among the land use types underscores the substitution of ecological land by “expansive” cultivation and construction lands. The value transfer matrix reveals that cultivated and construction lands have continuously experienced positive value inflows, whereas the service values of ecological lands such as forests and grasslands have suffered considerable losses, highlighting the competitive pressure exerted by economic expansion on ecological space;

(3)

The overall level of economic–ecological coordination remains low with pronounced regional disparities. Against the backdrop of water scarcity and uneven development, most prefectures, with the exception of a few regions (e.g., early-stage Hotan), exhibit low or negative economic–ecological coordination in later periods, emphasizing the conflict wherein economic growth outpaces the restoration of ecological functions;

(4)

The MOP and NSGA-III optimization revealed the trade-off between economic and ecological objectives. Under hard constraints such as water resource and ecological area constraints, the Pareto frontiers obtained from the three objectives (economic benefits, ecological benefits, and the coordination index) indicate that an ecologically prioritized scheme can significantly enhance the ESV, albeit at the expense of economic gains. Conversely, an economically prioritized scheme amplifies the GDP output but imposes a greater sacrifice on ecological functions. A balanced scheme can partially accommodate both, although the overall ESV remains lower than that achieved under an ecologically prioritized approach.