Developing a system for comprehensive regional Eco-environmental quality assessment in mountainous areas—A case study of Western Sichuan, China

Chen, Xiaojie; Chen, Shengbin; He, Zhengwei; Deng, Xue; Fang, Guozheng; Pan, Kaiwen; Fang, Kun

doi:10.3389/fenvs.2022.879662

Cited by 5 publications

(4 citation statements)

References 49 publications

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“…where SC p and SC r are potential and actual soil erosion (t•hm −2 ), respectively; R is the rainfall erosivity factor (MJ•mm/hm 2 •a); K represents the soil erodibility factor (t•hm 2 •a/MJ hm 2 •mm); LS is the slope length and steepness coefficients (dimensionless); C is the vegetation cover factor (dimensionless); and R, K, C and LS parameters have been shown in the equation of calculation in a previous study [48].…”

Section: Soil Retentionmentioning

confidence: 99%

Delineating Priority Areas for Preservation and Restoration across Production–Living–Ecological Spaces in Ganzi, China

Chen,

Deng,

et al. 2024

Sustainability

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Delineating conservation priority areas for both preservation and restoration is essential for developing adaptive ecosystem management strategies across production–living–ecological spaces (PLES). This study developed a coherent framework with four steps: (1) mapping spatial distributions of biodiversity and ecosystem services, (2) ranking the relative importance of ecosystems across spaces, (3) delineating priority areas for preservation and restoration according to the human footprint and priority ranks, and (4) contrasting with current conservation networks and overlapping with PLES. This framework was applied in Ganzi, China, to delineate the preservation priority areas (PPAs) of 8714.2 km2 and 11,308.1 km2, and restoration priority areas (RPAs) of 36,817.7 km2 and 63,578.4 km2 under the target to conserve 30% and 50% of territories, respectively. The priority areas, including PPAs and RPAs, achieve higher conservation capacity than the current Ecological Conservation Redline (ECR) in terms of biodiversity conservation or ecosystem service delivery. Roughly 67% of PPAs, 40% of RPAs, and a total of 75% of large patches with high priority are covered by ECR, indicating the necessity to adjust boundary and conduct restoration for ECR. As for PLES, the conservation priority areas encompass proportionally more ecological space (67–76%) than ECR (63.5%) or Ganzi (61.4%), implying the lower potential conflict between local residents’ production and conservation, and meanwhile, new opportunities and challenges in sustainable development in human-dominated spaces. The coherent framework to delineate PPAs and RPAs is flexible in terms of threshold in human impact or ecological degradation and can be improved by considering the complex relationships between indicators of biodiversity and ecosystem services. This study highlights the importance of incorporating ecosystem features, land uses, and human activities in developing different strategies according to different conservation purposes in the context of sustainable development.

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Section: Soil Retentionmentioning

confidence: 99%

Delineating Priority Areas for Preservation and Restoration across Production–Living–Ecological Spaces in Ganzi, China

Chen,

Deng,

et al. 2024

Sustainability

Self Cite

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“…The weight assignment of a resistance factor is an important link with which to accurately express the overall resistance of a region. Most of the previous studies on ecological resistance assignments used the analytic hierarchy process (AHP) [57][58][59]. However, this method is more subjective and does not consider the actual spatial situation of the region.…”

Section: Ecological Sources Characteristics and Assignment Of Resista...mentioning

confidence: 99%

Balancing Urban Expansion and Ecological Connectivity through Ecological Network Optimization—A Case Study of ChangSha County

Liu

Xia

et al. 2023

Land

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The counties have experienced urban expansion and landscape pattern fragmentation. As carriers of new urbanization, the balanced development between urban expansion and landscape connectivity in the counties needs to be emphasized. The uncontrolled expansion of land should be discouraged and planners need to clarify land use expansion patterns. Using Changsha County as the study area, the characteristics of the landscape pattern between 2000 and 2020 were analyzed. The morphological spatial pattern analysis and landscape connectivity method (CMSPACI), as well as the minimum cumulative resistance (MCR) model, was used to construct the ecological network. We also explored the most appropriate corridor width using the buffer zone to guide future land use planning and ecological network planning. The results show that based on CMSPACI the total area of ecological sources identified was 304.91 km2, encompassing a large area of forest parks. The total length of the 25 ecological corridors identified by the MCR model was 431.97 km. Ecological sources and corridors are missing in the central region; so, their pattern was optimized using landscape connectivity and the absence of location as selection criteria. The optimized network indices showed significant improvement. The width of the ecological corridors should be controlled in order to be in the range of 30 m to 50 m to maximize the effect of the corridors on species dispersal and migration. Our proposed research framework for the construction and optimization of EN in Changsha County can provide ideas to balance the contradictions between urban expansion and landscape connectivity in Changsha County.

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“…In terms of spatial distribution pattern simulations, previous studies [27] have not been able to simulate land use patches of natural land use types dynamically and spatially. Commonly used models include the Cellular Automata (CA) model [28,29], Conversion of Land Use and its Effects at Small Regional Extent (CLUE-S) model [30,31], and Future Land Use Simulation Model Software V2.4 (FLUS) [32][33][34][35][36][37][38][39][40][41][42][43][44]. However, PLUS not only retains the advantages of adaptive inertia competition and roulette competition mechanisms found in existing future land use simulation models but also utilizes the random forest algorithm to determine the development potential of each land use type.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, in the realm of dynamic modeling of land use change, numerous scholars have utilized land use data to assess habitat quality. This assessment is primarily conducted through hierarchical analysis (AHP) [42], artificial neural network methods (ANN) [43], principal component analysis [44], the InVEST model [45], RS-GIS Unified Ecological and Environmental Quality Evaluation index method [46], and other similar approaches. Notably, the InVEST model offers a concise method to estimate habitat quality based on land use data and habitat threat data.…”

Section: Introductionmentioning

confidence: 99%

Future Land Use Spatial Conflicts and Habitat Quality Impacts Based on SSPs-RCPs Scenarios—Qin-Ba Mountain City

Li,

Cheng,

Wang

et al. 2023

Land

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In the future, the pursuit of high-quality economic development and a focus on ecological environmental protection in China will inevitably result in significant conflicts between land use and ecological land use. Land use conflicts primarily occur in peri-urban areas characterized by prominent economic development and urban agglomeration. As a municipality situated in the Qin-Ba mountainous region, Ankang has been promoting ecological preservation for a span of two decades. The allocation of construction areas primarily focuses on the proximity of watersheds, while the northern and southern regions are predominantly characterized by mountainous and hilly terrain, thus exhibiting distinct regional attributes. Previous studies have mainly focused on analyzing the effects of land use on habitat quality during intense urbanization, with fewer studies focusing on integrating eco-regions with urbanization to assess changes in habitat quality. However, it is important to recognize that land pressure encompasses economic, ecological, and social aspects. Additionally, it aims to provide insights for the harmonious development of land use in eco-region-oriented cities. Using the SSPs-RCPs scenarios provided by the sixth phase of the Coupled Model Intercomparison Project (CMIP6), this paper employs a system analysis method, the emerging Patch-Generating Land Use Simulation model (PLUS) model, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and Land Use Conflict Measurement model to dynamically simulate the future habitat quality and spatial conflict patterns of land use in Ankang City. The study explores the spatial coupling effect of both factors under different scenarios. The results indicate the following: (1) The overall development trend reveals an intensification of land use conflicts and a decrease in habitat quality. The expansion rate of construction land is increasing and exhibiting aggregation, while agricultural land area is expanding, and forest land area is continuously decreasing. (2) Land use intensity exhibits a significant positive correlation with land conflict levels, while land conflict levels demonstrate a significant negative correlation with habitat quality. (3) Under different future shared socioeconomic path scenarios, land use intensity, and land conflict levels follow the order of SSP585 (high forcing scenario), SSP370 (medium to high forcing scenario), SSP245 (medium forcing scenario), and SSP126 (low forcing scenario), with intensity and conflict decreasing accordingly. These findings suggest that land use has had some impact on the ecological environment, with indications of habitat degradation. Even in Ankang, where ecological development is highly valued, the city will gradually face conflicts between ecological protection and economic development in future scenarios. The city already has the environment at heart, so it will be worse in cities where the priority is economic development. Therefore, it is crucial to allocate sufficient space for economic development while simultaneously prioritizing ecological protection. The results of the study can provide a reference for analyzing the trade-offs between land development and habitat protection in eco-mountainous cities and for eco-cities to avoid falling into the conflict dilemma of economic cities.

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Developing a system for comprehensive regional Eco-environmental quality assessment in mountainous areas—A case study of Western Sichuan, China

Cited by 5 publications

References 49 publications

Delineating Priority Areas for Preservation and Restoration across Production–Living–Ecological Spaces in Ganzi, China

Delineating Priority Areas for Preservation and Restoration across Production–Living–Ecological Spaces in Ganzi, China

Balancing Urban Expansion and Ecological Connectivity through Ecological Network Optimization—A Case Study of ChangSha County

Future Land Use Spatial Conflicts and Habitat Quality Impacts Based on SSPs-RCPs Scenarios—Qin-Ba Mountain City

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