Evaluating the potential impacts of land use changes on ecosystem service value under multiple scenarios in support of SDG reporting: A case study of the Wuhan urban agglomeration

Peng, Kaifeng; Jiang, Weiguo; Ling, Ziyan; Hou, Peng; Deng, Yawen

doi:10.1016/j.jclepro.2021.127321

Cited by 145 publications

(57 citation statements)

References 53 publications

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“…There have been many studies about the impact of LULC change on ES [29][30][31], and most of them focus on assessing the overall sensitivity of ES to LULC change [32,33], or analyzing the driving process of LULC changes affecting ES based on temperature, precipitation, population, and economy [34][35][36]. However, most studies only regard LULC changes as the result of land policy or human activities, and fail to distinguish between natural and human-induced processes in land cover changes.…”

Section: Introductionmentioning

confidence: 99%

Land Use and Land Cover Change in the Yellow River Basin from 1980 to 2015 and Its Impact on the Ecosystem Services

Liu

Pan

et al. 2021

Land

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Land use and land cover change is an important driving force for changes in ecosystem services. We defined several important human-induced land cover change processes such as Ecological Restoration Project, Cropland Expansion, Land Degradation, and Urbanization by the land use / land cover transition matrix method. We studied human-induced land cover changes in the Yellow River Basin from 1980 to 2015 and evaluated its impact on ecosystem service values by the benefit transfer method and elasticity coefficient. The results show that the cumulative area of human-induced land cover change reaches 65.71 million ha from 1980 to 2015, which is close to the total area of the Yellow River Basin. Before 2000, Ecological Restoration Project was the most important human-induced land cover change process. However, due to the large amount of cropland expansion and land degradation, the area of natural vegetation was reduced and the ecosystem value declined. Since 2000, due to the implementation of the "Grain for Green" program, the natural vegetation of upstream area and midstream area of Yellow River Basin has been significantly improved. This implies that under an appropriate policy framework, a small amount of human-induced land cover change can also improve ecosystem services significantly.

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Section: Introductionmentioning

confidence: 99%

Land Use and Land Cover Change in the Yellow River Basin from 1980 to 2015 and Its Impact on the Ecosystem Services

Liu

Pan

et al. 2021

Land

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“…Therefore, Xie et al [ 24 ] conducted a questionnaire survey of domestic ecologists and revised the coefficient table based on that of Costanza et al [ 19 ]. Compared with other methods, this method is considered more practical and has the advantages of low data requirements, high comparability of results, and the ability for comprehensive evaluation, and it has been widely used for ESV assessments in China [ 15 , 25 , 26 ]. Therefore, in this study we selected 11 ecosystem services to study the trends of ESV changes based on the classification system of Xie et al [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

“…This has driven the evolution of Wuhan’s spatial pattern in the landscape, leading to a rapid urbanization period with large-scale population migration [ 28 , 29 ]. However, this evolution has exposed the landscape to the pressures and challenges of the continuous expansion of built-up land and the accelerated degradation of ecological land, and has brought about many eco-environmental problems, such as lake reclamation, water pollution, and farmland erosion [ 5 , 25 ]. These human activities have disrupted the ecological balance of the lake and reduced its self-regulating capacity, thus leading to frequent urban flooding and even inducing catastrophic weather in local areas [ 21 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

Landscape Evolution and It’s Impact of Ecosystem Service Value of the Wuhan City, China

Chen

Huang

2021

IJERPH

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Rapid urbanization and industrialization and enhanced ecological protection measures have greatly influenced landscape change, which has exacerbated regional landscape competition and conflicts and indirectly affected the supply of ecosystem services. Clarifying the relationship between ecosystem service change and landscape change is useful for understanding the impact of ecosystem conversion on socio-economic development and providing a knowledge base for relevant policy decisions. In this study, we used remote sensing technology to process Landsat TM/ETM+/OLI imageries, combined with transformation analysis and kernel density analysis to study the spatial and temporal characteristics of land use change in Wuhan City from 1980 to 2020. We also estimated the ESV in the region using the improved unit area value equivalent method to reveal the trends of ESV changes in Wuhan. The results showed that land use changes in Wuhan during 1980–2020 occurred mainly in terms of decreases in farmland, forestland, and bare land, as well as increases in built-up land and water bodies. The built-up land was mainly concentrated in the main urban areas, but its area in each suburban area has increased in recent years. In contrast, farmland was mainly distributed in suburban areas, and its area has been decreasing in recent years due to the impact of urban expansion. However, the reduction is compensated for by the reclamation of ecological land such as grassland and forestland, which has aggravated the loss of ecosystem service values in the study area. In addition, human activities such as urban expansion have increased the demand for water resources, while also leading to ecological problems such as water scarcity and water quality degradation, which have caused serious losses to key ecosystem services in Wuhan city. Therefore, in order to alleviate the competition and conflicts in the landscape and mitigate the loss of ecosystem service values in this area, we have proposed some constructive suggestions for future urban planning and water quality improvements in Wuhan. The focus of these suggestions is on controlling the expansion of built-up land, as well as the conservation of ecological land and resource protection. Meanwhile, our findings can also provide reference information for land resource planning and ecological monitoring, and help researchers to understand the contribution of ecosystem service functions in relation to socio-economic development.

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“…Second, the simulation accuracy of spatial characteristics needs to be improved. Spatial characteristics are key to the CLUE-S model to assess the potential for land-use changes, which was calculated from land-use data and driving factors by logistic regression [51,56], autologistic regression [52,57,58], NE-Logistic regression [56], artificial neural networks [51] and random forest (RF) [53,59], and so forth. Some studies have shown that machine learning methods such as RF have higher simulation accuracy compared to traditional logistic regression [53], but no systematic comparisons have been made.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Simulation of Mangrove Forests under Different Scenarios: A Case Study of Mangrove Protected Areas, Hainan Island, China

2021

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Mangrove forests are important woody plant communities that grow in the intertidal zone between land and sea. They provide important social, ecological and economic services to coastal areas. In recent years, the growth environment of mangrove forests has been threatened. Mangrove forests have become one of the most endangered ecosystems in the world. To better protect mangrove forests, effective monitoring methods are essential. In this study, a spatio-temporal simulation method for mangrove forests was proposed in the mangrove protected areas of Hainan Island, China. This method compared the simulation accuracy of different models in terms of spatial characteristics, evaluated the applicability of driving factors in mangrove simulation and predicted the future spatio-temporal distribution and change trends of mangrove forests under different scenarios. The simulation results of different models showed that AutoRF (random forest with spatial autocorrelation) performs best in spatial characteristic simulation. Driving factors such as the Enhanced Vegetation Index (EVI), various location indices and the spatial autocorrelation factor can significantly improve the accuracy of mangrove simulations. The prediction results for Hainan Island showed that the mangrove area increased slowly under a natural growth scenario (NGS), decreased significantly under an economic development scenario (EDS) and increased significantly under a mangrove protection scenario (MPS) with 4460, 2704 and 5456 ha respectively by 2037. The contraction of mangrove forests is closely related to the expansion of aquaculture ponds, building land and cultivated land. Mangrove contraction is more severe in marginal or fragmented areas. The expansion of mangrove forests is due to the contraction of aquaculture ponds, cultivated land and other forests. The areas around existing mangrove forests and on both sides of the riverbank are typical areas prone to mangrove expansion. The MPS should be the most suitable development direction for the future, as it can reasonably balance economic development with mangrove protection.

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Evaluating the potential impacts of land use changes on ecosystem service value under multiple scenarios in support of SDG reporting: A case study of the Wuhan urban agglomeration

Cited by 145 publications

References 53 publications

Land Use and Land Cover Change in the Yellow River Basin from 1980 to 2015 and Its Impact on the Ecosystem Services

Land Use and Land Cover Change in the Yellow River Basin from 1980 to 2015 and Its Impact on the Ecosystem Services

Landscape Evolution and It’s Impact of Ecosystem Service Value of the Wuhan City, China

Spatio-Temporal Simulation of Mangrove Forests under Different Scenarios: A Case Study of Mangrove Protected Areas, Hainan Island, China

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