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Article

Enhancing Ecological Security in Ili River Valley: Comprehensive Approach

by
Ruyi Pan
1,2,
Junjie Yan
1,2,*,
Qianqian Xia
1,2 and
Xufan Jin
1,2
1
School of Resources and Environment, Yili Normal University, Yining 835000, China
2
Institute of Resources and Ecology, Yili Normal University, Yining 835000, China
*
Author to whom correspondence should be addressed.
Water 2024, 16(13), 1867; https://doi.org/10.3390/w16131867
Submission received: 3 May 2024 / Revised: 19 June 2024 / Accepted: 24 June 2024 / Published: 29 June 2024
(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)
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Abstract

:
The growing tension between economic development and ecological preservation in the Ili River Valley underscores the need for advanced analytical methods to effectively balance these interests. In this study, we utilized the InVEST model to quantify ecosystem services, combined with an analysis of ecological sensitivity, to comprehensively assess the ecological health of the region. By applying circuit theory, the research identified key ecological components such as sources, corridors, and critical nodes, alongside barriers; thus, mapping an ecological security pattern tailored specifically for the wetland oasis of the Ili River Valley. The analysis identified 15 ecological source sites covering 43,221.17 km2, 31 ecological corridors totaling 782 km in length, and 32 vital ecological nodes each exceeding 1 km2. Notably, 81.8% of these ecological source areas exhibited high ecological resilience, thus emphasizing their crucial role in maintaining the region’s ecological balance. The findings provide essential guidance for the ecological stewardship and management of the Ili River Valley and underscore the importance of incorporating ecological considerations within economic planning frameworks in arid regions.

1. Introduction

In the 21st century, the rapid expansion of urbanization and industrialization has led to significant detrimental impacts on ecological systems, including biodiversity depletion, degradation of ecosystem services, and increased ecological vulnerability [1]. These challenges threaten the development of national economies and societies, highlighting the urgent need for ecosystem restoration and functional optimization. In response to these needs, the concept of Ecological Security Patterns (ESP) has been developed, serving as a strategic framework not only for landscape planning but also for management that directly addresses the relationship between landscape structure and ecological function [2]. By focusing on the restoration of degraded ecosystems through structural optimization, ESP not only achieves rehabilitation but also bolsters resilience, providing a foundational approach for practical implementation. This strategy has not only guided practical applications but has also spurred further research into identifying and delineating urban ecological networks, thus advancing the design and enhancement of ecological networks in diverse geographical contexts such as plains and watersheds.
The research framework for ESP is structured around three critical phases: identification of ecological sources, creation of resistance surfaces, and extraction of ecological corridors [3]. Among these, identifying ecological sources forms the foundation [4]. Traditional methods often use land use data to identify areas rich in grassland and forest [5], or utilize Morphological Spatial Pattern Analysis (MSPA) models [6]. However, these approaches sometimes fail to capture the complex dynamics of ecosystems. Traditional land use methods rely on static data and simplified classifications, missing temporal changes and interactions within ecosystems. Similarly, MSPA, while effective in mapping structural connectivity, focuses primarily on the physical arrangement of landscape elements and does not incorporate the ecological functionality or sensitivity of these areas. This limitation can lead to an incomplete representation of ecosystem dynamics, as MSPA cannot assess how well different areas support ecological processes and respond to environmental stressors. In this paper, we present a comprehensive evaluation of ecosystem services and sensitivities, aimed at precisely identifying critical ecological source areas [7,8]. Recognizing the complex interplay among ecosystems, we have selected regions noted for their robust service provision and minimal ecological sensitivity. Through integrating a synergistic quantification approach, we aim to maintain service continuity and enhance resilience against disturbances [9]. Another critical phase involves constructing ecological resistance surfaces [10]. Our method incorporates both natural and anthropogenic factors, including the Remote Sensing-based Ecological Index (RSEI) and road density, to reflect nuanced variations in land use and their interactions with human activities [11]. This approach effectively maps the impediments faced by migrating species. Following the development of resistance surfaces, this research delineates ecological corridors using circuit theory. Ecological corridors are recognized as essential landscape features that facilitate the dispersal and migration of species and ensure the maintenance of ecological and evolutionary processes. These corridors often connect protected areas or habitats, enhancing biodiversity through the facilitation of animal migration, plant propagation, and genetic exchange [12]. Circuit theory surpasses traditional least-cost path methods by capturing the randomness of species movement and quantitatively evaluating landscape barriers [13]. Through refining Least-Cost Distance (LCD) models and implementing All-to-One configurations, our findings elucidate ecological connectivity and reveal the complex interdependencies within ecosystems [14,15]. By refining Least-Cost Distance (LCD) models, implementing All-to-One configurations, and other methods, our findings elucidate ecological connectivity and reveal the complex interdependencies within ecosystems. This provides a robust theoretical foundation for ecological restoration efforts [16,17].
Current methodologies are proficient in mapping the structural connectivity of ecosystems. However, they inadequately reflect the ecosystems’ ability to adapt to environmental, economic, and social changes. Consequently, to enhance the unification of the ecological security pattern and facilitate effective ecological restoration, we have integrated a comprehensive assessment of ecological resilience into our research framework [18]. This integration enables us to identify and prioritize regions within the ecological network that are vital for restoration, with a particular focus on areas exhibiting weak ecological resilience. Targeted interventions in these areas aim to improve both the connectivity and robustness of the ecological network system. The enhancement of ecological resilience ensures that ecosystems not only preserve their functions under environmental stress but also recover swiftly, thus supporting the refinement of the ecological security pattern and the sustainability of ecological restoration efforts [19]. Furthermore, this synergy between resilience assessment and ESP planning significantly bolsters the overall robustness of ecosystems and ensures their continued functionality and stability amid future environmental challenges [20]. Therefore, augmenting the ecological resilience indicator is essential, serving both as a supplement to existing methodologies and as a crucial component of ecological safety and restoration strategies. It enables ecosystems to endure and adapt to ongoing environmental changes [21]. This research not only identifies and prioritizes crucial restoration areas within the ecological network but also emphasizes targeted interventions in regions with diminished ecological resilience, enhancing system connectivity. This approach underscores the synergistic benefits of integrating resilience assessments with ecological network planning, markedly improving the ecosystem’s robustness.
The Ili Valley is a critical wetland in Central Asia, crucial for maintaining ecological stability in the region. The valley is not only a significant area for biodiversity and ecological conservation but is also a key hub for traditional livestock farming, and it is known for its abundant ecological resources [22]. It provides crucial habitats for endangered species listed on the IUCN Red List, including the Ili pika (Ochotona iliensis, national protection level: second-class, IUCN status: EN—Endangered) [23], and the four-clawed tortoise (Testudo horsfieldii, national protection level: first-class, IUCN status: VU—Vulnerable) [24]. Additionally, the Ili Valley is home to globally recognized natural heritage sites such as Kanas and Nalati, reflecting its significant value in global biodiversity conservation and natural heritage preservation. However, as the region becomes a strategic economic corridor in the “Belt and Road” initiative, it faces ecological challenges such as declining biodiversity, increased risks to endangered species, and meadow degradation due to traditional grazing practices, underscoring the urgent need to balance economic development with ecological conservation [25]. Through previous studies, we have identified several deficiencies in the management of the overall ecological security system of the Ili River Valley. For instance, the study by Wuşman et al. details the spatio-temporal changes in vegetation cover but does not adequately integrate these changes with broader ecological functions [26]. Similarly, Sui’s work on habitat quality under future climate scenarios offers valuable predictive insights yet fails to fully integrate these predictions with actionable conservation strategies [27]. While the research by Yu provides a focused analysis of the Ili River Valley’s vulnerability from the perspective of geological hazards, it largely neglects the broader ecological system’s interconnected elements and dynamics [28]. These studies collectively provide a foundational understanding yet fall short of creating a comprehensive and actionable ecological conservation framework that meets both the immediate and strategic ecological needs of the Ili Valley. In contrast, this research advances existing knowledge by developing a robust, integrated approach that assesses the current state of ecological functions and aligns them with sustainable conservation strategies.
The construction of the Ecological Security Patterns (ESP) for the Ili River Valley focuses on several specific objectives: (1) Identify crucial ecological source areas by integrating evaluations of ecosystem services and ecological sensitivity; (2) Construct resistance surfaces and extract ecological corridors using circuit theory, employing various models to identify ecological nodes within the Ili Valley; (3) Ensure that the conservation outcomes of ecological source areas align with key biodiversity conservation areas, protect biodiversity, promote the restoration of degraded grasslands, and propose optimized strategies for implementing ESP. Additionally, the approach includes reserving ample space for future economic development.

2. Materials and Methods

2.1. Study Area

The Ili Valley, located in northwestern China between 42°14′16″ N to 44°53′30″ N and 80°9′42″ E to 84°56′50″ E, features a unique geographic structure known as “three mountains, two valleys, one basin” (Figure 1). The valley’s vertical climatic zoning is pronounced, with low-altitude deserts, mid-altitude meadows, and high-altitude scrub and coniferous forests. This unique ecological gradient not only bolsters regional biodiversity but also provides essential ecological services to the inhabitants. Climate conditions vary widely across the valley; average annual temperatures range from −4 °C to 9 °C, and annual precipitation varies from 200 mm to 800 mm [29]. Moisture levels are higher in the eastern mountains, resulting in greater precipitation, while the western plains experience drier conditions. Despite the natural diversity, human activities have led to the degradation of grasslands, threatening biodiversity and undermining the ecological resilience and long-term sustainability of the region. Moreover, the “Large-scale development of the Western Region” initiative has spurred rapid economic growth, putting substantial pressure on this fragile ecological environment. Addressing the challenge of reconciling economic advancement with ecological preservation has thus become crucial.

2.2. Data Sources

Indicators in this study are selected based on the following reasons, and the data used are all from 2020:
1. Biodiversity Conservation: The Ili Valley hosts a unique array of flora and fauna, including several endangered species, making it a priority area for conservation. Monitoring Land Use Type, NDVI, and Soil Type is essential for tracking the impacts of human activity on these habitats and for assessing changes in ecological health that could threaten biodiversity sustainability.
2. Natural Factors: The unique mountain climate and intricate terrain of the Ili Valley significantly influence both ecological and economic dynamics. The Digital Elevation Model (DEM) is pivotal for mapping and understanding these geographical impacts. It facilitates an assessment of how topography affects local climate, water flow, and biodiversity, which are crucial for sustainable agriculture and livestock practices. Additionally, Average Annual Precipitation and the Remote Sensing Ecological Index (RSEI) are vital for monitoring climate variability. These indicators track changes in precipitation and ecological conditions impacting water availability and pasture quality. Together, they offer a comprehensive perspective that supports ecological health assessments, informs conservation strategies, and assists in adapting agricultural planning to climate fluctuations.
3. Human Impact: As the Ili Valley becomes increasingly integrated into broader economic initiatives like the ”Belt and Road” initiative, the pressures of urbanization and infrastructure development intensify. Indicators such as Roads, GDP, and Night Lights help quantify these changes, offering insights into the pace of development and its alignment with sustainable practices.
We explore a variety of challenges in the Ili River Valley, including the escalating conflict between economic growth and ecological preservation and the increasing impact of human activities on ecosystem stability. To address these issues, we have constructed ecological security patterns for the Ili River Valley, with all data standardized to a 500-m resolution (Table 1).

2.3. Methods

In this paper, we implemented a systematic approach to develop ESP for the Ili River Valley (Figure 2). The process began with an evaluation of ecosystem services, including biodiversity, water resources, and soil conservation, combined with an assessment of the area’s ecological sensitivity to identify crucial ecological source areas. This assessment integrated natural elements, such as topography and vegetation, with human activity indicators like road density to create an ecological resistance surface that identifies barriers to ecological flow. Using circuit theory, we mapped ecological corridors, nodes, and critical barriers, thereby establishing vital pathways for ecological connectivity. Additionally, we evaluated the region’s ecological resilience by considering natural, social, and economic factors, resulting in a comprehensive ESP that aims to bolster ecosystem stability and resilience while providing strategic insights for sustainable ecological management.

2.3.1. Identification of Ecological Source Areas

Ecosystem services comprise the diverse natural products and environmental resources that ecosystems provide for societal use [30]. In the Ili River Valley, by utilizing the InVEST model, we quantified key factors such as biodiversity, water yield, soil retention, habitat quality, carbon sequestration, and water production. Water yield is calculated by evaluating vegetation net primary productivity and soil moisture saturation [31]. Soil retention is estimated by comparing potential soil erosion with actual soil deposition [32]. Habitat quality reflects the ecosystem’s capacity to support species survival, reproduction, and interaction, directly linked to biodiversity [33]. Carbon sequestration involves the capture and storage of atmospheric carbon dioxide [34], and water production measures the capture and storage of precipitation as water resources [35]. To optimize data processing efficiency, all factors were converted into 500-meter resolution raster images. We normalized the six ecosystem services to eliminate scale differences between them. Next, we utilized the raster calculator in ArcGIS to equally weight and sum these six services. Finally, we applied the natural breaks classification method to categorize the aggregated results into five distinct classes, thereby forming a comprehensive evaluation of the ecosystem services.
Ecological sensitivity demonstrates an ecosystem’s responsiveness to disturbances from human activities and natural environmental changes [36]. Within the Ili River Valley, considering human, natural, and geographical factors, seven key elements were identified to assess ecological sensitivity: elevation, slope, aspect, bodies of water, vegetation, soil type, and land use type. The Analytic Hierarchy Process (AHP) was employed, employing the yaahp software to calculate and validate the consistency of each factor’s weights, as detailed in Table 2 [37].
The evaluation of ecological protection significance combines spatial overlays of ‘high’ and ‘relatively high’ ecosystem service outcomes with ‘non-sensitive’ and ‘low sensitivity’ assessments derived from the ecological sensitivity evaluation. This integration provides the foundation for identifying ecological source areas. Initially, numerous small and fragmented patches were identified using ArcGIS tools for aggregation and face elimination; these were consolidated into preliminary source areas. Subsequently, a threshold for patch size and number was established, and patches falling below this threshold were excluded. The remaining patches were then identified as ecological source areas.

2.3.2. Construction of Resistance Surfaces, Corridor Identification

Influential natural factors on ecological quality, such as greenness, wetness, temperature, and dryness, are closely linked to human activities and daily life [38]. These factors not only serve as direct measures of ecological quality but can also be accurately quantified using remote sensing data [39]. The Remote Sensing Ecological Index (RSEI), which includes four important indicators—Greenness, Wetness, Dryness, and Heat [40]—has been adopted in this paper as one of the main indices for the ecological resistance surface, as proposed by Professor Hanqiu Xu [11]. Given the extensive area of the study region, this research employed Landsat 8 imagery from the GEE platform, implementing procedures for cloud removal, anomaly removal, and masking to prepare the image data. Subsequently, the Wetness Index (WET), Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Normalized Difference Built-up and Soil Index (NDBSI) were calculated. The resulting RSEI image was then generated through Principal Component Analysis (PCA), as detailed in Table 3.
Determining resistance factors and coefficients is crucial for creating a resistance surface, which represents the barriers to species migration and energy exchange [41]. To accurately reflect the unique characteristics of the study area and include both natural and socio-economic influences, factors such as elevation, slope, land classification, and road density were selected as indicators. These factors were categorized into five levels using the natural break method. Weights for each factor were established through the Analytic Hierarchy Process (AHP), and their validity was confirmed by a consistency check. A comprehensive resistance surface was subsequently derived through weighted summation, as detailed in Table 4.
Ecological corridors are narrow strips within the ecological landscape that primarily function as the main conduits for gene flow and species propagation among populations [42]. We extracted ecological corridors using the circuit theory model implemented through Linkage Mapper.

2.3.3. Identification of Ecological Pinch Points and Barrier Points

Using the connectivity model of circuit theory, we conceptualize the landscape pattern as a conductive surface where species movements resemble electrical currents. Land cover types that support ecological processes are assigned low resistance values, while those that impede these processes receive high resistance values [43]. Regions critically affecting the stability of regional ecological processes, known as ‘pinch points’, are crucial for ecological protection [44]. In this study, we used the Circuitscape software and its Pinchpoint Mapper tool to identify these ecological pinch points. Furthermore, ecological barrier points, which are areas within ecosystems where biological movement encounters significant resistance, were also identified. Restoring these points can significantly enhance landscape connectivity between source areas [45]. The Barrier Mapper tool within Linkage Mapper (LM) identifies barrier points that either completely block or partially impede ecological flows [46].

2.3.4. Identification of Ecological Resilience

Ecosystems with high ecological resilience are characterized by robust self-sustenance and self-regulation capabilities [18]. Consequently, developing a comprehensive resilience indicator system is crucial for performing resilience assessments [47] We identified ten factors across natural, economic, and social dimensions that influence ecological resilience, specifically tailored to regional characteristics and inclusive of both positive and negative impacts [48]. The weights for these factors were determined through the Analytic Hierarchy Process (AHP) and expert scoring. The results were subsequently classified into five categories—low, relatively low, medium, high, and relatively high—using the natural break method(Table 5).

3. Result

3.1. Ecological Identification

3.1.1. Calculation of Ecosystem Services

The Ili River Valley features generally high habitat quality, with an average value of 0.61, as shown in Figure 3a. High-quality habitats are primarily found in extensive forested and grassland areas, particularly in the north-south blocks and patches of the valley. In contrast, low-quality displays exhibit a band-like distribution along the cultivated lands adjacent to the Ili and Gongnaisi Rivers, around Narat Grassland, and in parts of the Zhaosu Basin. Due to the valley’s temperate continental climate and topography, precipitation is limited and temperatures are elevated, resulting in generally low water yield (Figure 3b); higher water yields are observed at greater latitudes and elevations. In 2020, carbon storage in the Ili River Valley peaked at 1020.05 Tg, with an average of 57.25 Tg (Figure 3d). The highest storage areas are located in vegetated mountainous regions, including Koguchin Mountain, Polokonu Mountain, Ushun Mountain, and Tianshan. Conversely, areas with minimal carbon storage, primarily glaciers, and unused lands, are located along the valley’s northern and southern fringes. Biodiversity is robust throughout the valley, with an average biodiversity index of 0.56 (Figure 3c), and is particularly abundant in grassland-rich regions. Soil and water conservation functions are primarily concentrated in the forest and grassland zones at the foothills and near significant ecological landmarks such as Narat Grassland and Ushun Mountain (Figure 3e,f). These vegetation-rich areas are crucial for sustaining regional ecological functions.
The comprehensive assessment of ecosystem services indicates that areas with very high and high service levels collectively make up 30.53% of the total study area (Figure 4). These vital zones are predominantly located in the mountainous northern and southern regions, as well as near the eastern trumpet-shaped mouth of the valley, and are crucial for water conservation and soil preservation efforts. Medium service level areas, which account for 39.08% of the study area, are found across regions with varying grassland coverage, including Horgos City, Yining County, and northern Tekes County. These areas offer viable opportunities for ecological conservation and are essential for restoration initiatives. Conversely, regions with lower ecological service levels, often adjacent to unused lands with minimal vegetation, underscore a pressing need for targeted management and conservation strategies.

3.1.2. Calculation of Ecological Sensitivity

Elevation and slope significantly impact biodiversity and habitat quality in the Ili River Valley (Figure 5). As these factors increase, there is a general decline in biodiversity and habitat quality, along with reduced soil cohesion, which exacerbates soil erosion and heightens ecological sensitivity. The aspect of the slope is influenced by a complex interplay of sunlight, precipitation, and wind speed, creating a diverse ecological environment. Furthermore, there is a notable positive correlation between water bodies and ecological sensitivity; water bodies, primarily concentrated along the Ili River and its major tributaries, make these areas more ecologically sensitive. In contrast, vegetation exhibits a negative correlation with ecological sensitivity. The abundant vegetation and its structural diversity in the valley positively affect ecological regulation during the growth season, effectively reducing ecological sensitivity.
In the moist, organic-rich plains and low-altitude foothills of the Ili River Valley, land use and soil types generally exhibit lower ecological sensitivity, while the outer boundaries of the valley show higher sensitivity. According to the comprehensive ecological sensitivity assessment depicted in Figure 6, non-sensitive and low-sensitivity areas constitute 52.52% of the study area. These regions are primarily found within agricultural lands and high-coverage grassland areas. Non-sensitive zones are notably prevalent on gentle slopes, whereas low-sensitivity areas appear as small, scattered patches along the edges, demonstrating both strong water conservation and soil preservation capabilities. Moderate sensitivity areas, which comprise 24.7% of the study area, occur mostly in low-coverage grasslands characterized by sparse vegetation and limited soil and water conservation potential. The high and moderately high sensitivity areas, which account for 22.78% of the study area, are primarily situated in unused lands at the valley’s periphery. These regions are ecologically fragile and have limited restoration capacity, underscoring the urgent need for enhanced protective measures to safeguard these critical ecological spaces.
Ecological source areas were derived by evaluating the comprehensive importance of ecosystem services and ecological sensitivity (Figure 7). Following data aggregation and spatial processing, 15 key ecological source areas were identified, comprising 39.23% of the study area. These areas are primarily situated along the peripheries of the Ili River Valley, notably around the Koguchin, Polokonu, and Tianshan Mountain Ranges, as well as the eastern trumpet-shaped mouth featuring the Aural Mountain Range and Narat Grassland. Other significant areas include those near Chapchal Xibe Autonomous County and Gongliu County, located centrally within the valley and adjacent to the Ushun Mountain Range.
These areas feature high vegetation coverage, providing essential services for water conservation and biodiversity protection that are crucial for sustaining ecosystem health. The ecological source areas feature robust landscape connectivity with a well-distributed network of ecological patches, enhancing species migration and genetic flow. Additionally, these regions have low population densities, which minimally impact human activities, thereby supporting the sustainability of ecosystem services and ecological balance. As a result, these ecological source areas are vital for ecological protection and restoration, requiring focused attention and robust protection measures to preserve the ecological security and biodiversity of the Ili River Valley.

3.2. Setting of Resistance Surfaces

We developed an ecological resistance surface by identifying five key factors, emphasizing grasslands as a crucial ecological element due to their widespread distribution (Figure 8). We utilized the Remote Sensing Ecological Index (RSEI) as an inverse factor in the resistance surface calculation, where higher values indicated better ecological conditions and, therefore, lower resistance. Principal Component Analysis (PCA) of the RSEI demonstrated that the first principal component (PC1) encapsulated most attributes from the four indicators, accurately reflecting the area’s ecological status (Table 6). Greenness and wetness positively influenced the ecological quality, whereas dryness and heat had detrimental effects. The composite resistance surface (Figure 8f) showed that areas along the Ili, Gongnaisi, Kashgar, and Tekes Rivers, as well as regions with dense vegetation, exhibited low resistance, thereby facilitating species movement and ecological service delivery. In contrast, unused lands at the valley’s periphery and zones of high human activity showed high resistance, threatening ecosystem health and species migration. These high-resistance areas require targeted management to enhance ecological capacity and safeguard biodiversity and ecological processes from the impacts of human activities.

3.3. Extraction of Ecological Corridors

This paper presents a comprehensive analysis of ecological source areas and the development of a composite resistance surface in the Ili River Valley, where we identified 31 ecological corridors using the Linkage Mapper tool. These corridors span a total of 782 km, averaging 50.45 km each. The corridor lengths vary significantly, with the longest extending 87.31 km and the shortest measuring just 0.35 km; 17 corridors exceed 10 km in length. Their strategic distribution along water bodies, grasslands, and forests underscores the vital role these natural features play in facilitating ecological connectivity.
The specific distribution of these corridors shows that longer corridors primarily extend in a north-to-south longitudinal orientation, aligned with river systems such as the Ili, Kashgar, and Tekes Rivers, and display distinct linear characteristics. In contrast, the shorter corridors mainly traverse through grasslands and forests, with some displaying a west-to-east orientation. The complex network of long and short corridors forms an integrated system that significantly enhances species migration and gene flow. This robust ecological network structure is crucial for sustaining ecosystem health and promoting biodiversity across the region.

3.4. Extraction of Ecological Pinch Points and Barrier Points

This study utilized the Pinch-Point Mapper tool to identify ecological pinch points in the Ili River Valley using two configurations: ‘allToOne’ and ‘allpairs’. In the ‘allToOne’ configuration (Figure 9a), the peak current density reached 3.58865, typically concentrated at junctions between corridors and source areas. Conversely, in the ‘allpairs’ mode (Figure 9b), the maximum current density was 4.7564, with currents more uniformly distributed along the corridors. An analysis using the natural break method revealed 96 ecological pinch points, with approximately 74% identified under the pairwise configuration. These pinch points are primarily found in low-resistance areas such as rivers, grasslands, and forests, which are crucial for enhancing the ecological network. Pinch points at the intersections of corridors and source areas are especially vital for network connectivity and thus require targeted protection to maintain ecosystem integrity.
The Barrier Mapper tool was utilized to pinpoint ecological barrier points. In the unimproved score mode (Figure 10a), high-scoring areas, critical for linking ecological source areas with corridors, are predominantly located in the northern corridor sections. These areas are essential for bolstering ecological connectivity across the Ili River Valley. In contrast, under the improved score mode (Figure 10b), the current density is more evenly spread, with significant points clustered at source patch junctions. Using the natural break method, 68 ecological barrier points were identified—56 from the unimproved mode—covering 169.4 square kilometers. Among these, 48 barrier points, each smaller than 1 square kilometer, are prioritized for restoration to enhance landscape connectivity. Conversely, the 12 larger barrier points, each over 5 square kilometers and situated in areas of high human activity or with sparse to moderate grassland coverage, pose significant restoration challenges and require focused intervention.

4. Discussion

4.1. Integration of Ecological Resilience to Construct and Assess the Ecological Security Pattern

Building on the foundational work by [49], which evaluated overall ecosystem health, this paper delves deeper into the regional determinants of ecological resilience, identifying specific areas in need of restoration. This refined analysis facilitates tailored conservation strategies, ensuring more effective resource allocation and enhancing the health and service capacity of ecosystems in affected regions, as noted by [50]. The overall ecological resilience of the Ili River Valley remains noteworthy (Figure 11). However, areas such as Yining City and its environs, subject to frequent human activity, exhibit diminished resilience due to prolonged overgrazing and developmental pressures. This situation underscores the urgent need for targeted ecological restoration efforts.
Building on the findings of [51], who emphasized the impact of altitudinal conditions and diverse ecological drivers on the distribution of ecological source areas, we developed the ESP system for the Ili Valley. Our analysis identified ecological source areas that closely align with key biodiversity protection zones and distinctive landscape features. An examination of the relationship between these ecological source areas and resilience reveals that a substantial portion—81.8% of their total area—is located in regions of medium to high resilience. This observation highlights the effectiveness and stability of the designated ecological source areas. As a result, these areas are not only essential for providing habitats for rare and at-risk species but also play a crucial role in promoting the restoration of degraded grasslands, curbing the unwarranted expansion of agricultural lands, and maintaining ecological balance.
While safeguarding biodiversity, we carefully consider the unique geographical and ecological attributes of the alluvial fan region in the Ili Valle [14], recognizing it as a crucial zone for prospective economic development. Situated along the banks of principal rivers, including areas such as Yining City and Khorgas, this alluvial fan zone is characterized by its lower elevation and superior ecosystem services. These features provide significant geographical advantages for urban and economic expansion, thereby laying a solid foundation for the future growth of the Ili Valley.
Overall, we have successfully established the ESP system that strategically allocates spaces for both future economic development and ecological protection. This approach embodies a philosophy that equally values ecological conservation and the stimulation of economic growth [52]. This strategic framework not only supports the protection and restoration of ecosystems but also promotes the symbiotic advancement of ecological health and regional economic vitality [53].

4.2. Optimizing the Ecological Network

The ecological security of the Ili River Valley is closely linked to its economic stability. As the valley undergoes rapid economic expansion, driven by national strategies like the Western Development Drive and the Belt and Road Initiative, it faces increasing environmental pressures. These pressures include the expansion of farmland and urban areas, excessive water extraction for agricultural and industrial purposes, and the encroachment on natural oases, leading to reduced watershed runoff and the degradation of grasslands and forests (Liu et al., 2021). This paper proposes several strategies to enhance the ecological security of the Ili River Valley, stemming from a comprehensive analysis:
1. Establish a Safe Ecological Network: Improve connectivity by linking biodiversity conservation belts and ecosystem conservation belts across key areas like the Koguchin-Borokonu Mountains, Harkitau Mountain–Narat Mountain, and Ushun Mountain. Focus on reconstructing wetlands and restoring aquatic vegetation, leveraging the ecological potential of the valley’s numerous rivers to enhance conservation efforts and scenic value.
2. Restore Degraded Grasslands: Implement reforestation, grassland restoration, and wetland recovery in areas with scant vegetation, such as low mountain regions, plains, and basins. These initiatives aim to harmonize agricultural productivity with ecological restoration needs [54]. Simultaneously, it reduces the extent of farmlands and pastures, enhances their quality, and improves agricultural infrastructure. Strategically plan pastoral areas, promote the relocation of agricultural and pastoral communities to centralized residential zones, and manage the scale and intensity of agricultural and livestock activities to minimize ecological strain.
3. Restore the Ecological Bottleneck Area: Apply ecological red lines in regions with low ecological resilience, notable vegetation degradation, and high ecological sensitivity. Focus on enhancing vegetation conditions by establishing protective forests in plains, conducting strategic afforestation, and strengthening the soil and water conservation and windbreak functions of vegetation, thus fostering a robust ecological wetland.
This paper defines the ESP as “three belts, two zones, and three nodes” (Figure 12). The three ecological source belts are determined by the locations of key ecological source areas; the two essential restoration zones are delineated based on attributes including diminished ecological restoration capacity and extensive grassland degradation; the three ecological node restoration areas are identified in regions characterized by significant ecological bottlenecks and barriers. By developing an ecological network pattern, the strategy integrates the natural ecosystems of the Ili River Valley seamlessly, establishing a comprehensive ESP that encompasses various ecological nodes and corridors. This network not only facilitates the systematic implementation of the security pattern but also highlights the unique ecological framework of the Ili River Valley.

4.3. Limitations of the Study

Significant progress has been made in developing the ESP in the Ili River Valley. However, several limitations were identified. First, the current research does not adequately address the valley’s diverse aquatic ecosystems, especially the habitats supporting various rare fish species. Future research should aim to incorporate the ESP to include these critical habitats. Second, due to the spatial heterogeneity of the landscape, the dimensions and configurations of ecological corridors may vary [55]. Future studies could benefit from considering various perspectives on threshold settings for corridor configurations.
In conclusion, despite these limitations, our work contributes valuable insights and experiences to the development and enhancement of the ESP in the Ili River Valley. By addressing the identified gaps, subsequent research can more precisely evaluate and enhance ecological restoration and protection efforts in the region, supporting more effective strategies for sustainable development.

5. Conclusions

In this paper, we applied a comprehensive methodology to assess and enhance the ESP of the Ili River Valley, resulting in significant findings:
1. Ecosystem Services and Sensitivity Analysis: We used the InVEST software to integrate six critical ecological factors—habitat quality, soil retention, water conservation, water yield, carbon sequestration, and biodiversity—with seven sensitivity factors—slope, aspect, elevation, water bodies, vegetation, soil type, and land use type. This integration effectively identified 15 key ecological source areas, accounting for 39.23% of the total area. These areas are primarily located in regions with high ecosystem service values and low ecological sensitivity, encompassing grasslands and forests of substantial ecological importance.
2. Ecological Resistance Surface and Corridor Identification: We used factors such as the Remote Sensing Ecological Index (RSEI), elevation, slope, road density, and land use type to create a resistance surface. Using the Linkage Mapper software, we identified 31 ecological corridors that facilitate species migration and biodiversity conservation. Additionally, the study recognized 96 ecological pinch points and 68 barrier points, which identified 32 priority ecological nodes for restoration, spanning a total area of 279.32 square kilometers, primarily along river basins and in areas of frequent human activity.
3. Ecological Resilience Analysis: By developing an ecological resilience assessment model incorporating natural, social, and economic factors, we discovered that most ecological source areas (81.8%) exhibit medium to high resilience, indicating robust stability and recovery potential for the ecosystems of the Ili River Valley.
The outcomes of this research not only provide a scientific foundation for ecological protection and sustainable development within the Ili River Valley but also provide effective methodologies and strategies for constructing the ESP in similar arid wetland regions. Through detailed assessment and optimization of key ecological source areas, corridors, and resilience, this paper underscores the critical role of ecosystem service functions, fosters the development of ecological networks, and establishes a strong basis for promoting sustainable ecological advancement.

Author Contributions

Conceptualization, R.P.; Methodology, R.P., J.Y., and Q.X.; Software, R.P. and X.J.; Validation, X.J.; Writing—original draft, R.P.; Writing—review and editing, R.P., J.Y. and Q.X.; Visualization, R.P. and X.J.; Supervision, J.Y. and Q.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Institute of Resources and Ecology, Yili Normal University, Open Project (YLNURE202209), the Basic and cross-cutting frontier scientific research pilot projects of Chinese Academy of Sciences (XDB0720100), Natural Science Foundation of Xinjiang Uygur Autonomous Region (2023D01D18), Key Research and Development Project of Xinjiang (2022B03024-1), Science and Technology Planning Project of Xinjiang Production, Construction Corps (2022DB023) and Tianshan Talent Training Program (2023TSYCLJ0047).

Data Availability Statement

The relevant data can be found in this article.

Conflicts of Interest

All authors declare no conflicts of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

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Figure 1. (a) Location of the Ili River Valley in Xinjiang and the elevation map. (b) Location of Xinjiang within China.
Figure 1. (a) Location of the Ili River Valley in Xinjiang and the elevation map. (b) Location of Xinjiang within China.
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Figure 2. Methodological process framework.
Figure 2. Methodological process framework.
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Figure 3. Ecosystem services: HQ represents habitat quality, WY represents water yield, CS represents carbon storage, SC represents soil conservation, and WC represents water conservation.
Figure 3. Ecosystem services: HQ represents habitat quality, WY represents water yield, CS represents carbon storage, SC represents soil conservation, and WC represents water conservation.
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Figure 4. Integrated ecosystem service function: (a) Integrated ecosystem services; (b) Corresponding level area.
Figure 4. Integrated ecosystem service function: (a) Integrated ecosystem services; (b) Corresponding level area.
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Figure 5. Ecological sensitivity.
Figure 5. Ecological sensitivity.
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Figure 6. Comprehensive evaluation of ecological sensitivity: (a) Comprehensive ecological sensitivity; (b) Corresponding level area.
Figure 6. Comprehensive evaluation of ecological sensitivity: (a) Comprehensive ecological sensitivity; (b) Corresponding level area.
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Figure 7. Ecological source.
Figure 7. Ecological source.
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Figure 8. Resistance surface.
Figure 8. Resistance surface.
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Figure 9. Pincipoint Mapper-based ecological pinch analysis: (a) allpairs; (b) all To One.
Figure 9. Pincipoint Mapper-based ecological pinch analysis: (a) allpairs; (b) all To One.
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Figure 10. Analysis of Ecological Obstacle Points Based on Barrier Mapper: (a) Percentage of unimproved score relative to LCD; (b) Percentage improvement in score relative to LCD.
Figure 10. Analysis of Ecological Obstacle Points Based on Barrier Mapper: (a) Percentage of unimproved score relative to LCD; (b) Percentage improvement in score relative to LCD.
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Figure 11. The ecological security pattern of the Ili River Valley: (a) Integrated resilience coupled with ecological network; (b) Ecological sources vs. resilience areas; (c) Ecological network.
Figure 11. The ecological security pattern of the Ili River Valley: (a) Integrated resilience coupled with ecological network; (b) Ecological sources vs. resilience areas; (c) Ecological network.
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Figure 12. Ecological spatial framework planning.
Figure 12. Ecological spatial framework planning.
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Table 1. Data sources and descriptions.
Table 1. Data sources and descriptions.
Data TypeClarificationSource of Data
Land use type 1. Jie Yang, and Xin Huang. The 30 M Annual Land Cover Datasets and Its Dynamics in China from 1985 to 2022. Earth System Science Data. Zenodo, 1 August 2023: 2. Institute of Geographic Sciences and Resources, Chinese Academy of Sciences: www.igsnrr.cas.cn (2022 edition)
Digital Elevation Model (DEM)DEM was used to further calculate the slope, slope direction, and river system dataASTER Global Digital Elevation Model V002: https://search.earthdata.nasa.gov/search?q=ASTER (2022 edition) (accessed on 2 May 2024)
RoadsCreation of road density calculations for fishing netsOpenStreetMap
Soil typeCutting, reclassificationHome | Food and Agriculture Organization of the United Nations (fao.org) (2022 edition)
AtmosphereAverage annual precipitationNational Tibetan Plateau Science Data Centre: https://data.tpdc.ac.cn/ (accessed on 13 June 2023)
Normalized Vegetation Index (NDVI)normalizationChina Ecological Science Data Centre: http://www.nesdc.org.cn/sdo/list (accessed on 15 August 2023)
Night LightsStandard deviation stretchNOAA EOG: NOAA/NGDC—Earth Observation Group: ngdc.noaa.gov (accessed on 5 March 2022)
Soil organic carbon content, effective soil water contentIncludes data on soil surface and subsoil contentHengl, T., MacMillan, R.A. (2019). Predictive Soil Mapping with R. OpenGeoHub foundation, Wageningen, the Netherlands, 370 pages, ISBN: 978-0-359-30635-0
Gross regional product (GDP)Plotted from an Excel sheet imported into an ArcGIS attribute table.Xinjiang Statistical Yearbook: https://tjj.xinjiang.gov.cn/tjj/zhhvgh/list_nj1.shtml (2022 edition) (accessed on 2 May 2024)
RSEICalling of Landsat 8 satellite imagery for June-August 23 through the GEE platformGoogle Earth engine.https://developers.google.cn/earth-engine/ (June to August 2023)
Table 2. Evaluation factors for ecological sensitivity indicators.
Table 2. Evaluation factors for ecological sensitivity indicators.
SensitivitiesAltitudeElevationSlope DirectionBody of WaterPlant CoverSoil TypeLand Use TypeHierarchy
Non-sensitive53–1300Level ground, due southLevel ground, due south>500 m0.8–0.99Marshy soils, grey meadow soilsBuilt-up and unused land1
Hypoallergenic1300–2000South-east, South-westSouth-east, South-west500–1000 m0.6–0.8Black calcium soilGrassland2
Medium-sensitive2000–2800RampEast, West1000–1500 m0.4–0.6Calcium chestnut soilArable land3
Highly-sensitive2800–3500Steep inclineNorth-east, north-west1500–2000 m0.2–0.4Grey-calcium Soil, grey-brown soilWoodland4
Higher-sensitive3500–6317Rapid and dangerous slopesMain north<2000 m0–0.2Inland saline Soils, glaciersWater Bodies and glaciers5
Weights0.130.10.090.170.210.160.14
Table 3. Remote sensing ecological indicators calculation formula.
Table 3. Remote sensing ecological indicators calculation formula.
NormCount
Normalized Difference Vegetation Index (NDVI) NDVI = ( ρ _ NIR   −   ρ _ RED ) / ( ρ _ NIR + ρ _ RED )
Dryness Barrier Indicator (NDBSI) NDSBI = ( SI + IBI ) / 2
SI = ( ( ρ SWIR 1 + ρ RED ) − ( ρ BLUE + ρ NIR ) ) ( ( ρ SWIR 1 + ) + ( ρ BLUE + ρ NIR ) )
IBI = ( 2 ρ SWIR 1 / ( ρ SWIR 1 + ρ NIR ) − ( ρ NIR / ( ρ NIR + ρ RED ) + ρ GREEN / ( ρ GREEN + ρ SWIR 1 ) ) ) ( 2 ρ SWIR 1 / ( ρ SWIR 1 + ρ NIR ) + ( ρ NIR / ( ρ NIR + ρ RED ) + ρ GREEN / ( ρ GREEN + ρ SWIR 1 ) ) )
Humidity indicator (WET) Wet = 0.1147   B 1 + 0.2489 B 2 + 0.3132 B 3   0.3122 B 4   −   0.6416 B 5   −   0.5087 B 6
Heat metrics (LST)This indicator is expressed in terms of surface temperature (LST)
LST = ( LST _ Day _ 30 m + LST _ Night _ 30 m ) / 2
Table 4. Resistance factors and resistance values.
Table 4. Resistance factors and resistance values.
Drag Factor Resistance Value Weights
12345
Land use typeBody of waterWoodlandGrasslandResidential and unused landArable land0.3518
RSEI1–0.70.7–0.60.6–0.40.4–0.20.2–00.2666
Road density0–0.280.28–0.850.85–1.911.91–4.664.66–12.930.2021
Altitude530–2811281–0132013–27212721–34443444–63170.1021
Slope0–4.444.44–10.7410.74–17.7517.75–25.9225.92–59.320.0744
Table 5. Ecological resilience factors and weights.
Table 5. Ecological resilience factors and weights.
Evaluation FactorWeightsAffect (Usually Adversely)
Natural factorTopographic relief0.0568Negative direction
Vegetation cover0.1758Forward
Measured quantity of rain0.2328Forward
Surface soil organic carbon content0.0449Forward
Sub-surface soil organic carbon content0.0556Forward
The effective water content of surface soil0.0464Forward
The effective water content of subsurface soil0.0568Forward
Social and economic factorsGross regional product (GDP)0.1229Negative direction
Road density0.1023Negative direction
Night Lights0.1058Negative direction
Table 6. RSEI principal component analysis.
Table 6. RSEI principal component analysis.
Component IndicatorPC1PC2PC3PC4
NDVI0.8640.4630.195−0.036
WET0.397−0.400−0.823−0.073
LST−0.3050.791−0.531−0.016
NDBSI−0.056−0.0010.061−0.997
Eigenvalue (math.)0.0520.01240.0040.000007
% contribution75.6417.996.360.01
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Pan, R.; Yan, J.; Xia, Q.; Jin, X. Enhancing Ecological Security in Ili River Valley: Comprehensive Approach. Water 2024, 16, 1867. https://doi.org/10.3390/w16131867

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Pan R, Yan J, Xia Q, Jin X. Enhancing Ecological Security in Ili River Valley: Comprehensive Approach. Water. 2024; 16(13):1867. https://doi.org/10.3390/w16131867

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Pan, Ruyi, Junjie Yan, Qianqian Xia, and Xufan Jin. 2024. "Enhancing Ecological Security in Ili River Valley: Comprehensive Approach" Water 16, no. 13: 1867. https://doi.org/10.3390/w16131867

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Pan, R., Yan, J., Xia, Q., & Jin, X. (2024). Enhancing Ecological Security in Ili River Valley: Comprehensive Approach. Water, 16(13), 1867. https://doi.org/10.3390/w16131867

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