IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i8p1270-d882632.html
   My bibliography  Save this article

Simulation Analysis of Land-Use Pattern Evolution and Valuation of Terrestrial Ecosystem Carbon Storage of Changzhi City, China

Author

Listed:
  • Lijun Xie

    (School of Land Science and Technology, China University of Geoscience, Haidian District, Beijing 100083, China)

  • Zhongke Bai

    (School of Land Science and Technology, China University of Geoscience, Haidian District, Beijing 100083, China
    Key Lab of Land Consolidation and Rehabilitation, The Ministry of Natural Resources, Beijing 100035, China)

  • Boyu Yang

    (School of Land Science and Technology, China University of Geoscience, Haidian District, Beijing 100083, China)

  • Shuai Fu

    (School of Land Science and Technology, China University of Geoscience, Haidian District, Beijing 100083, China)

Abstract

Carbon sequestration in terrestrial ecosystems is critical for combating global climate change and achieving regional carbon neutrality, and LUCC is a vital factor influencing the carbon cycle process of terrestrial ecosystems and causing changes in carbon sources/sinks. This study analyzes the drivers of LUCC based on a review of the dynamics of LUCC in Changzhi from 2000 to 2020, analyzes the driving factors of LUCC using the Clue-S model and binary logistic regression analysis model, then simulates land-use patterns under different scenarios in 2030 by the CA-Markov model, and finally analyzes carbon stock changes and spatial distribution characteristics in different periods from the perspective of carbon source/sink interconversion with the help of InVEST model. The results show: (1) in the past two decades, more than 90% of the expansion of artificial surfaces in Changzhi comes from cultivated land. Ecological conservation policies are more decisive in influencing LUCC than natural, social, and transportation accessibility factors. (2) During the 20 years, the total carbon stock increased by 680,989.73 t, with the carbon emission control area accounting for 7.5%, mainly distributed near urban centers and coal mining areas. The carbon sink enhancement area accounts for 5.5% and is mainly concentrated near forest land and ecological and nature reserves. (3) The spatial location of cities influences the density of carbon stock in the adjacent range. Carbon stock density increases within the buffer zone with the distance from urban center, county center, expressways, national highway, settlements, rivers, provincial roads, reservoirs, railways, county highway, and village roads. The rate of carbon stock increase per 100 m is 0.12 t/ha, 0.25 t/ha, 0.17 t/ha, 0.36 t/ha, 0.71 t/ha, 0.33 t/ha, 0.38 t/ha, 0.57 t/ha, 0.23 t/ha, 0.46 t/ha, and 0.48 t/ha respectively. The higher the administrative center and road grades, the lower the carbon density will be instead. (4) In the 2030 CD scenario, compared with the ND scenario, the cultivated land and grassland are effectively protected and the cultivated land area is increased by 445.68 km 2 , while the expansion of artificial surface is suppressed and the area is reduced by 448.2 km 2 , which ultimately leads to a reduction in carbon loss of 392,011.85 t. Future ecological management should focus on protecting high-value carbon sink areas and carbon sink enhancement areas and the ecological management and restoration of low-value carbon sink areas and carbon emission control areas.

Suggested Citation

  • Lijun Xie & Zhongke Bai & Boyu Yang & Shuai Fu, 2022. "Simulation Analysis of Land-Use Pattern Evolution and Valuation of Terrestrial Ecosystem Carbon Storage of Changzhi City, China," Land, MDPI, vol. 11(8), pages 1-31, August.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1270-:d:882632
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/8/1270/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/8/1270/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kevin Robert Gurney & Rachel M. Law & A. Scott Denning & Peter J. Rayner & David Baker & Philippe Bousquet & Lori Bruhwiler & Yu-Han Chen & Philippe Ciais & Songmiao Fan & Inez Y. Fung & Manuel Gloor , 2002. "Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models," Nature, Nature, vol. 415(6872), pages 626-630, February.
    2. Birch, Colin P.D. & Oom, Sander P. & Beecham, Jonathan A., 2007. "Rectangular and hexagonal grids used for observation, experiment and simulation in ecology," Ecological Modelling, Elsevier, vol. 206(3), pages 347-359.
    3. Xin, Liangjie & Li, Xiubin, 2018. "China should not massively reclaim new farmland," Land Use Policy, Elsevier, vol. 72(C), pages 12-15.
    4. Shilong Piao & Jingyun Fang & Philippe Ciais & Philippe Peylin & Yao Huang & Stephen Sitch & Tao Wang, 2009. "The carbon balance of terrestrial ecosystems in China," Nature, Nature, vol. 458(7241), pages 1009-1013, April.
    5. Xu, Hongtao & Song, Youcheng & Tian, Yi, 2022. "Simulation of land-use pattern evolution in hilly mountainous areas of North China: A case study in Jincheng," Land Use Policy, Elsevier, vol. 112(C).
    6. Wang, Jieyong & Zhang, Ziwen & Liu, Yansui, 2018. "Spatial shifts in grain production increases in China and implications for food security," Land Use Policy, Elsevier, vol. 74(C), pages 204-213.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Jianjun & Wei, Chen & Adamowski, Jan F. & Zhou, Junju & Liu, Chunfang & Zhu, Guofeng & Dong, Xiaogang & Zhang, Xiaofang & Zhao, Huijun & Feng, Qi, 2020. "Could arid and semi-arid abandoned lands prove ecologically or economically valuable if they afford greater soil organic carbon storage than afforested lands in China’s Loess Plateau?," Land Use Policy, Elsevier, vol. 99(C).
    2. Liu, Yansui & Zhou, Yang, 2021. "Reflections on China's food security and land use policy under rapid urbanization," Land Use Policy, Elsevier, vol. 109(C).
    3. Zhou, Yang & Li, Xunhuan & Liu, Yansui, 2020. "Land use change and driving factors in rural China during the period 1995-2015," Land Use Policy, Elsevier, vol. 99(C).
    4. Chen, Hang & Meng, Fei & Yu, Zhenning & Tan, Yongzhong, 2022. "Spatial–temporal characteristics and influencing factors of farmland expansion in different agricultural regions of Heilongjiang Province, China," Land Use Policy, Elsevier, vol. 115(C).
    5. De Yu & Shougeng Hu & Luyi Tong & Cong Xia, 2020. "Spatiotemporal Dynamics of Cultivated Land and Its Influences on Grain Production Potential in Hunan Province, China," Land, MDPI, vol. 9(12), pages 1-22, December.
    6. Lanhui Li & Pingshan Jiang & Wenfeng Liu & Yaxin Sun & Zhanhao Dang, 2022. "Increasing Spatial Mismatch of Cropland-Grain Production-Population in China over the Past Two Decades," Land, MDPI, vol. 11(10), pages 1-14, September.
    7. Denis Maragno & Michele Dalla Fontana & Francesco Musco, 2020. "Mapping Heat Stress Vulnerability and Risk Assessment at the Neighborhood Scale to Drive Urban Adaptation Planning," Sustainability, MDPI, vol. 12(3), pages 1-16, February.
    8. Shixiong Song & Siyuan Zhao & Ye Zhang & Yongxi Ma, 2023. "Carbon Emissions from Agricultural Inputs in China over the Past Three Decades," Agriculture, MDPI, vol. 13(5), pages 1-12, April.
    9. Jieming Chou & Yidan Hao & Yuan Xu & Weixing Zhao & Yuanmeng Li & Haofeng Jin, 2023. "Forest Carbon Sequestration Potential in China under Different SSP-RCP Scenarios," Sustainability, MDPI, vol. 15(9), pages 1-12, April.
    10. Li, Shuoshuo & Liu, Yaobin & Wei, Guoen & Bi, Mo & He, Bao-Jie, 2024. "Carbon surplus or carbon deficit under land use transformation in China?," Land Use Policy, Elsevier, vol. 143(C).
    11. Yan Zhou & Tao Chen & Jingjing Wang & Xiaolan Xu, 2023. "Analyzing the Factors Driving the Changes of Ecosystem Service Value in the Liangzi Lake Basin—A GeoDetector-Based Application," Sustainability, MDPI, vol. 15(22), pages 1-15, November.
    12. Kim, Suji & Lee, Sujin & Ko, Eunjeong & Jang, Kitae & Yeo, Jiho, 2021. "Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price," Journal of Transport Geography, Elsevier, vol. 96(C).
    13. Zhen, Wei & Qin, Quande & Miao, Lu, 2023. "The greenhouse gas rebound effect from increased energy efficiency across China's staple crops," Energy Policy, Elsevier, vol. 173(C).
    14. Pacheco de Castro Flores Ribeiro, Paulo & Osório de Barros de Lima e Santos, José Manuel & Prudêncio Rafael Canadas, Maria João & Contente de Vinha Novais, Ana Maria & Ribeiro Ferraria Moreira, Franci, 2021. "Explaining farming systems spatial patterns: A farm-level choice model based on socioeconomic and biophysical drivers," Agricultural Systems, Elsevier, vol. 191(C).
    15. Xinbei Huang & Chengming Ye & Hongyu Tao & Junjie Zou & Yuzhan Zhou & Shufan Zheng, 2024. "Integrating Future Multi-Scenarios to Evaluate the Effectiveness of Ecological Restoration: A Case Study of the Yellow River Basin," Land, MDPI, vol. 13(7), pages 1-19, July.
    16. Francesca Peroni & Guglielmo Pristeri & Daniele Codato & Salvatore Eugenio Pappalardo & Massimo De Marchi, 2019. "Biotope Area Factor: An Ecological Urban Index to Geovisualize Soil Sealing in Padua, Italy," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    17. Yu, Zhenning & She, Shuoqi & Xia, Chuyu & Luo, Jiaojiao, 2023. "How to solve the dilemma of China’s land fallow policy: Application of voluntary bidding mode in the Yangtze River Delta of China," Land Use Policy, Elsevier, vol. 125(C).
    18. Jue Wang & Mei-Po Kwan & Yanwei Chai, 2018. "An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago," IJERPH, MDPI, vol. 15(4), pages 1-24, April.
    19. Oliveira, Renata Lúcia Magalhães de & Dablanc, Laetitia & Schorung, Matthieu, 2022. "Changes in warehouse spatial patterns and rental prices: Are they related? Exploring the case of US metropolitan areas," Journal of Transport Geography, Elsevier, vol. 104(C).
    20. Sungsoo Yoon & Youngjoo Moon & Jinah Jeong & Chan-Ryul Park & Wanmo Kang, 2021. "A Network-Based Approach for Reducing Pedestrian Exposure to PM 2.5 Induced by Road Traffic in Seoul," Land, MDPI, vol. 10(10), pages 1-14, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1270-:d:882632. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.