Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China
Land use is a crucial factor affecting ecosystem service value (ESV), and forecasting future land use changes and ESV response can guide urban planning and sustainable development decisions. However, the traditional Cellular Automata (CA) model supposes that each cell has only one land use type at e...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-03-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23001516 |
| _version_ | 1828005313490452480 |
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| author | Ping Zhang Lei Liu Lianwei Yang Juan Zhao Yangyang Li Yuting Qi Xuenan Ma Lei Cao |
| author_facet | Ping Zhang Lei Liu Lianwei Yang Juan Zhao Yangyang Li Yuting Qi Xuenan Ma Lei Cao |
| author_sort | Ping Zhang |
| collection | DOAJ |
| description | Land use is a crucial factor affecting ecosystem service value (ESV), and forecasting future land use changes and ESV response can guide urban planning and sustainable development decisions. However, the traditional Cellular Automata (CA) model supposes that each cell has only one land use type at each time step, neglects the mixed structure and proportional distribution of land use units, does not take into account its quantitative continuous dynamic change, and lacks the exploration of land use quantity structure and spatial pattern optimization. This study employed a novel mixed-cell cellular automata (MCCA) approach, coupled with the system dynamics (SD) model to predict the spatiotemporal pattern of land use under the natural increase scenario (NIS), economic development scenario (EDS) and ecological protection scenario (EPS) in Xi’an, China, in 2030. The equivalent coefficient method was utilized to investigate the heterogeneity distribution and sensitivity of ESV. The results demonstrated that SD-MCCA exhibited remarkable prediction accuracy and robustness. The main changes in land use in 2000–2015 were due to urban expansion, the conversion of arable land into construction land, and the conversion between grassland and arable land. The total ESV increased from 19554.36×106 CNY in 2000 to 19618.39×106 CNY under the EPS in 2030, and the contribution of climate regulation and hydrological regulation to ESV was the highest. Spatial heterogeneity of ESV revealed a certain regularity, and the high value region was chiefly concentrated in woodland and grassland with favorable ecological conditions. Land use variations under NIS and EPS improved ESV, while the ESV had a negative response to land use transformations under the EDS. This research provides a new way to identify the relationship between future land utilization scenarios and ESV, which is of great significance for the management of land resources and formulation of ecological compensation standards. |
| first_indexed | 2024-04-10T07:29:06Z |
| format | Article |
| id | doaj.art-b13a87a19c4e42ef96576d492e5d3a53 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-10T07:29:06Z |
| publishDate | 2023-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-b13a87a19c4e42ef96576d492e5d3a532023-02-24T04:30:05ZengElsevierEcological Indicators1470-160X2023-03-01147110009Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, ChinaPing Zhang0Lei Liu1Lianwei Yang2Juan Zhao3Yangyang Li4Yuting Qi5Xuenan Ma6Lei Cao7School of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, China; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Shaanxi Key Laboratory of Land Consolidation, Xi’an 710075, China; State Key Laboratory of Green Building in Western China, Xi’an University of Architecture & Technology, Xi’an 710055, China; Xi’an Key Laboratory of Territorial Spatial Information, Xi’an 710075, China; Corresponding author.School of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaLand use is a crucial factor affecting ecosystem service value (ESV), and forecasting future land use changes and ESV response can guide urban planning and sustainable development decisions. However, the traditional Cellular Automata (CA) model supposes that each cell has only one land use type at each time step, neglects the mixed structure and proportional distribution of land use units, does not take into account its quantitative continuous dynamic change, and lacks the exploration of land use quantity structure and spatial pattern optimization. This study employed a novel mixed-cell cellular automata (MCCA) approach, coupled with the system dynamics (SD) model to predict the spatiotemporal pattern of land use under the natural increase scenario (NIS), economic development scenario (EDS) and ecological protection scenario (EPS) in Xi’an, China, in 2030. The equivalent coefficient method was utilized to investigate the heterogeneity distribution and sensitivity of ESV. The results demonstrated that SD-MCCA exhibited remarkable prediction accuracy and robustness. The main changes in land use in 2000–2015 were due to urban expansion, the conversion of arable land into construction land, and the conversion between grassland and arable land. The total ESV increased from 19554.36×106 CNY in 2000 to 19618.39×106 CNY under the EPS in 2030, and the contribution of climate regulation and hydrological regulation to ESV was the highest. Spatial heterogeneity of ESV revealed a certain regularity, and the high value region was chiefly concentrated in woodland and grassland with favorable ecological conditions. Land use variations under NIS and EPS improved ESV, while the ESV had a negative response to land use transformations under the EDS. This research provides a new way to identify the relationship between future land utilization scenarios and ESV, which is of great significance for the management of land resources and formulation of ecological compensation standards.http://www.sciencedirect.com/science/article/pii/S1470160X23001516Ecosystem service valueMCCASDScenario predictionSensitivity analysis |
| spellingShingle | Ping Zhang Lei Liu Lianwei Yang Juan Zhao Yangyang Li Yuting Qi Xuenan Ma Lei Cao Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China Ecological Indicators Ecosystem service value MCCA SD Scenario prediction Sensitivity analysis |
| title | Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China |
| title_full | Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China |
| title_fullStr | Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China |
| title_full_unstemmed | Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China |
| title_short | Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China |
| title_sort | exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed cell cellular automata model and system dynamics model in xi an china |
| topic | Ecosystem service value MCCA SD Scenario prediction Sensitivity analysis |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23001516 |
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