Dynamic State of Ecosystem Carrying Capacity Under Island Urbanization: A Case Study of Pingtan Island in the Southeastern Coast of China

Gao, Sheng; Sun, Hai; Cao, Guangxi; Zhao, Lin; Wang, Runjie; Xu, Min

doi:10.3846/jeelm.2020.9798

Cited by 6 publications

(5 citation statements)

References 19 publications

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“…Fortunately, the assessment methods of ordinary islands provide a reference for the comprehensive assessment of coral reef islands CC. These methods mainly include the system dynamics model 41 , ecological footprint method 42 , energy analysis 43 , 44 , and the comprehensive indicator system 45 , 46 . The system dynamics model can quantitatively analyse the intrinsic relationship between the structure and function of various complex systems; however, it is difficult to select the parameter indicator, and the large quantity of data limits the application of the model and the similitude to reality 47 .…”

Section: Introductionmentioning

confidence: 99%

Development of a comprehensive assessment model for coral reef island carrying capacity(CORE-CC)

Chen

Cheng

et al. 2021

Sci Rep

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Coral reef islands provide precious living space and valuable ecological services for human beings, and its sustainability cannot be ignored under the pressure of human activities. Carrying capacity (CC) assessment has gradually become an important means to measure sustainability of islands. However, there is little comprehensive evaluation of the carrying capacity of coral reef islands, and traditional evaluation methods are difficult to express the social-ecological characteristics of coral reef islands. The present paper proposes a comprehensive assessment model for coral reef island carrying capacity (CORE-CC) which comprises dimensions of resources supply, environmental assimilative, ecosystem services, and socio-economic supporting. According to the characteristics of the coral reef islands, the core factors and indicators of each dimension are selected and the corresponding assessment index system of "pressure-support" is constructed. The assessment involves (1) identification of carrying dimensions and core factors, (2) pressure/support measurement and (3) assessment of carrying state. A case study is conducted in Zhaoshu Island of China, demonstrating the applicability of CORE-CC model and serving as a reference for adaptive management.

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Section: Introductionmentioning

confidence: 99%

Development of a comprehensive assessment model for coral reef island carrying capacity(CORE-CC)

Chen

Cheng

et al. 2021

Sci Rep

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“…Therefore, this research mainly uses remote sensing data combined with GIS technology to establish an index evaluation system. When evaluating the ECC, most previous studies [37][38][39][40] used statistical data and administrative divisions as units. These methods are one-sided and lack specificity.…”

Section: Ecc Evaluation Methods and Data Acquisitionmentioning

confidence: 99%

Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

Zhu

Mei

et al. 2022

Land

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Ecological carrying capacity (ECC), which requires simple scientific evaluation methods, is an important evaluation index for assessing the sustainability of ecosystems. We integrate an innovative research method. Geographic information systems (GIS) and remote sensing (RS) were used to evaluate the ECC of the Yellow River Basin in Shaanxi (YRBS) and to identify the underlying factors that influence it. A calculation method that combines RS and GIS data to estimate ECC based on net primary productivity (NPP) was established. The Carnegie–Ames–Stanford approach model was applied to estimate NPP. The NPP of each land type was used as an indicator to determine the yield factors. The ECC of the watershed was calculated with the carrying capacities of each land-use type. The geographical detector model was used to study the influencing factors of ECC, which provides a scientific basis for the formulation of ecological management policies in YRBS. The results show that from 2000 to 2010, it first decreased by 45.46%, and then increased by 37.06% in 2020, an overall decrease of 13.49 × 105 wha in 20 years. Precipitation is the dominant factor that affects ECC, while the impact of human activities on ECC was significantly enhanced during the study period. The developed method based on RS data serves as a reference for ecological evaluation in other similar regions.

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“…Although the energy value analysis method can convert the indexes of different types and units of measurement into the same standard energy value for analysis, it is difficult to put forward the threshold value of the evaluation system 9 . The ecological footprint method is simple and feasible in the evaluation of the ecological environment, but it could not fully consider the impact of human technological progress and social development 10 . LCA can be used to evaluate the capacity of the ecosystem coordinated development.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of eco-environmental quality for the coal-mining region using multi-source data

Jiang

Fan

Zhang

et al. 2022

Sci Rep

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The contradiction between the exploitation of coal resources and the protection of the ecological environment in western China is becoming increasingly prominent. Reasonable ecological environment evaluation is the premise for alleviating this contradiction. First, this paper evaluates the eco-environment of Ibei coalfield by combining the genetic projection pursuit model and geographic information system (GIS) and using remote sensing image data and other statistical data of this area. The powerful spatial analysis function of GIS and the advantages of the genetic projection pursuit model in weight calculation have been fully used to improve the reliability of the evaluation results. Furthermore, spatial autocorrelation is used to analyze the spatial characteristics of ecological environment quality in the mining area and plan the specific governance scope. The geographic detector is used to determine the driving factors of the eco-environment of the mining area. The results show that Ibei Coalfield presents a spatially heterogeneous eco-environment pattern. The high-intensity mining area (previously mined area of Ili No.4 Coal Mine) has the worst ecological environment quality, followed by the coal reserve area of Ili No.4 Coal Mine and the planned survey area of Ili No.5 Coal Mine. The eco-environment quality (EEQ) of the study area is affected by both human and natural factors. Mining intensity and surface subsidence are the main human factors affecting the ecological environment in the study area. The main natural factors affecting the ecological environment in the study area are annual average precipitation, elevation, annual average evaporation, NDVI and land use type. Meanwhile, the interaction effect of any two indicators is greater than that of a single indicator. It is also indicated that the eco-environment of the mining area is nonlinearly correlated to impact indicators. The spatial autocorrelation analysis shows three areas that should be treated strategically that are the management area, close attention area and protective area. Corresponding management measures are put forward for different regions. This paper can provide scientific references for mining area eco-environmental protection, which is significant for the sustainability of coal mine projects.

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Dynamic State of Ecosystem Carrying Capacity Under Island Urbanization: A Case Study of Pingtan Island in the Southeastern Coast of China

Cited by 6 publications

References 19 publications

Development of a comprehensive assessment model for coral reef island carrying capacity(CORE-CC)

Development of a comprehensive assessment model for coral reef island carrying capacity(CORE-CC)

Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

Evaluation of eco-environmental quality for the coal-mining region using multi-source data

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