Dynamic simulation of land use change and assessment of carbon storage based on climate change scenarios at the city level: A case study of Bortala, China

• Published in: Ecological indicators Vol. 134; p. 108499
• Main Authors: Wang, Ziyao, Li, Xin, Mao, Yueting, Li, Liang, Wang, Xiangrong, Lin, Qing
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-01-2022; Elsevier
• Subjects: Carbon neutrality; Climate change; PLUS model; Scenario simulation; System dynamics model; Climate change; Scenario simulation; Carbon neutrality; System dynamics model; PLUS model
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2021.108499

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•We proposed an integrated framework combining SD, PLUS and InVEST models.•SSP-RCP scenarios were used to predict future changes in land use demand.•The future changes in land use and CS showed significant differences under the three scenarios.•CS can be increased by adjusting socio-economic and land use policies.
Exploring future changes in land use and carbon storage (CS) under different climate scenarios is important for optimizing regional ecosystem service functions and formulating sustainable socioeconomic development policies. We proposed a framework that integrates the system dynamics (SD) model, patch-generating land use simulation (PLUS) model, and Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST) model to dynamically simulate changes in land use/cover change (LUCC) and CS at the city level based on SSP-RCP scenarios provided by the CMIP6. The simulations were applied to Bortala Mongol Autonomous Prefecture in Xinjiang. Changes in LUCC were similar under the SSP126 and SSP245 scenarios, but woodland expansion was more rapid under the SSP126 scenario. Changes in LUCC under the SSP585 scenario were different from those under the other two scenarios, and this was mainly caused by the continuous reduction in woodland area and the rapid expansion of construction land and cultivated land. By 2050, the simulation results revealed that CS was highest under the SSP126 scenario (193.20 Tg), followed by the SSP245 scenario (192.75 Tg) and SSP585 scenario (185.17 Tg). Overall, the results of this study suggest that increases in CS could be achieved by controlling economic growth and population growth, promoting an energy transition, and expanding woodland in the study area.