Ecology and Environment

Evaluation and prediction of ecosystem carbon storage in the Inner Mongolia section of the Yellow River Basin based on the InVEST-PLUS model

  • LI Bingjie ,
  • FAN Zhitao ,
  • QU Zhicheng ,
  • YAO Shunyu ,
  • SU Xiashu ,
  • LIU Dongwei ,
  • WANG Lixin
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  • 1. School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, Inner Mongolia, China
    2. Key Laboratory of Mongolian Plateau Ecology and Resource Utilization, Ministry of Education, Hohhot 010021, Inner Mongolia, China

Received date: 2023-10-24

  Revised date: 2023-12-20

  Online published: 2024-08-01

Abstract

The carbon storage of terrestrial ecosystems plays a crucial role in mitigating global warming. Assessing the impact of land use changes on carbon storage in the Inner Mongolia section of the Yellow River basin can contribute to achieving “dual carbon” targets. This study applied the InVEST model to assess carbon storage in the Inner Mongolia section of the Yellow River basin over the past 20 years. The PLUS model was used to predict land use patterns in 2040 under three different development scenarios. The study then coupled the InVEST-PLUS to predict the carbon storage for the next 20 years, exploring the response relationship between land use changes and carbon storage. The results indicated that from 2000 to 2020, grasslands were the major land use type and the most significant carbon reservoir. The increase in grassland area was the primary reason for the total rise in carbon storage at 4.08×107 t. Under the ecological protection scenario, it is most conducive to improving carbon storage in the basin by 2040, with a total increase of 4.50×107 t. Annual precipitation was the factor with the single highest explanatory power. As socioeconomic development progresses, its explanatory power on the spatial and temporal differentiation characteristics of carbon storage becomes more apparent. The explanatory power of two-factor interactions is generally much higher than that of single factors for these characteristics. This study aims to provide recommendations for regional land planning and to help China achieve its carbon neutrality goals better.

Cite this article

LI Bingjie , FAN Zhitao , QU Zhicheng , YAO Shunyu , SU Xiashu , LIU Dongwei , WANG Lixin . Evaluation and prediction of ecosystem carbon storage in the Inner Mongolia section of the Yellow River Basin based on the InVEST-PLUS model[J]. Arid Zone Research, 2024 , 41(7) : 1217 -1227 . DOI: 10.13866/j.azr.2024.07.13

References

[1] Yu Guirui, Zhang Li, He Honglin, et al. A process-based model and simulation system of dynamic change and spatial variation in large-scale terrestrial ecosystems[J]. The Journal of Applied Ecology, 2021, 32(8): 2653-2665.
[2] Li Yiming, Yang Xue, Wu Bowen, et al. Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models[J]. PeerJ, 2023, 11(11): e15285.
[3] Liang Xun, Guan Qifeng, Clarke K C, et al. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China[J]. Computers, Environment and Urban Systems, 2021, 85(42): 101569.
[4] Churkina G, Brown D G, Keoleian G. Carbon stored in human settlements: The conterminous United States[J]. Global Change Biology, 2010, 16(1): 135-143.
[5] 付超, 于贵瑞, 方华军, 等. 中国区域土地利用/覆被变化对陆地碳收支的影响[J]. 地理科学进展, 2012, 31(1): 88-96.
  [Fu Chao, Yu Guirui, Fang Huajun, et al. Effects of land use and cover change on terrestrial carbon balance of China[J]. Progress In Geography, 2012, 31(1): 88-96.]
[6] Houghton R A. Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850-2000[J]. Tellus Series B: Chemical and Physical Meteorology, 2003, 55(2): 378-390.
[7] Hu Yanbin, Zhang Qiang, Hu Shujuan, et al. Research progress and prospects of ecosystem carbon sequestration under climate change (1992-2022)[J]. Ecological Indicators, 2022, 145(22): 109656.
[8] Houghton R A. Carbon emissions and the drivers of deforestation and forest degradation in the tropics[J]. Current Opinion in Environmental Sustainability, 2012, 4(6): 597-603.
[9] Kertész á, Nagy L A, Balázs B. Effect of land use change on ecosystem services in Lake Balaton Catchment[J]. Land Use Policy, 2019, 80(36): 430-438.
[10] Kantzas E P, Val Martin M, Lomas M R, et al. Substantial carbon drawdown potential from enhanced rock weathering in the United Kingdom[J]. Nature Geoscience, 2022, 15(5): 382-389.
[11] Zhou Junju, Zhao Yaru, Huang Peng, et al. Impacts of ecological restoration projects on the ecosystem carbon storage of inland river basin in arid area, China[J]. Ecological Indicators, 2020, 118(20): 106803
[12] Lü Yihe, Ma Zhimin, Zhao Zhijiang, et al. Effects of land use change on soil carbon storage and water consumption in an oasis-desert ecotone[J]. Environmental Management, 2014, 53(41): 1066-1076.
[13] Maanan M, Maanan M, Karim M, et al. Modelling the potential impacts of land use/cover change on terrestrial carbon stocks in north-west Morocco[J]. International Journal of Sustainable Development & World Ecology, 2019, 26(6): 560-570.
[14] Wang Rueiyuan, Cai Huina, Chen Lingkang, et al. Spatiotemporal evolution and Multi-Scenario prediction of carbon storage in the GBA based on PLUS-InVEST models[J]. Sustainability, 2023, 15(10): 8421.
[15] 朱文博, 张静静, 崔耀平, 等. 基于土地利用变化情景的生态系统碳储量评估—以太行山淇河流域为例[J]. 地理学报, 2019, 74(3): 446-459.
  [Zhu Wenbo, Zhang Jingjing, Cui Yaoping, et al. Assessment of territorial ecosytem carbon storage based on land use change scenario: A case study in Qihe River Basin[J]. Acta Geographica Sinica, 2019, 74(3): 446-459.]
[16] 丁岳, 王柳柱, 桂峰, 等. 基于InVEST模型和PLUS模型的环杭州湾生态系统碳储量[J]. 环境科学, 2023, 44(6): 3343-3352.
  [Ding Yue, Wang Liuzhu, Gui Feng, et al. Ecosytem carbon storage in Hangzhou bay area based on InVEST ang PLUS model[J]. Environmental Science, 2023, 44(6): 3343-3352.]
[17] 林彤, 杨木壮, 吴大放, 等. 基于InVEST-PLUS模型的碳储量空间关联性及预测——以广东省为例[J]. 中国环境科学, 2022, 42(10): 4827-4839.
  [Lin Tong, Yang Muzhuang, Wu Dafang, et al. Spatial correlation and prediction of land use carbon storage based on the InVEST-PLUS model: A case study in Guangdong Province[J]. China Environmental Science, 2022, 42(10): 4827-4839.]
[18] Liang Youjia, Hashimoto S, Liu Lijun. Integrated assessment of land-use/land-cover dynamics on carbon storage services in the Loess Plateau of China from 1995 to 2050[J]. Ecological Indicators, 2021, 120(21): 106939.
[19] Wang Zhuo, Zeng Jie, Chen Wanxu. Impact of urban expansion on carbon storage under multi-scenario simulations in Wuhan, China[J]. Environmental Science and Pollution Research, 2022, 29(30): 45507-45526.
[20] 卢大同. 强化黄河流域水生态治理保障黄河流域高质量发展[J]. 农业灾害研究, 2020, 10(6): 153-154.
  [Lu Datong. Strengthening water ecological management of the Yellow River basin to ensure high quality development of the Yellow River Basin[J]. Journal of Agricultural Catastrophology, 2020, 10(6): 153-154.]
[21] Wei Yiming, Chen Kaiyue, Kang Jianing, et al. Policy and management of carbon peaking and carbon neutrality: Aliterature review[J]. Engineering, 2022, 14(8): 52-63.
[22] Zhu Guofeng, Qiu Dongdong, Zhang Zhuanxia, et al. Land-use changes lead to a decrease in carbon storage in arid region, China[J]. Ecological Indicators, 2021, 127(21): 107770.
[23] 卢雅焱, 徐晓亮, 李基才, 等. 基于InVEST模型的新疆天山碳储量时空演变研究[J]. 干旱区研究, 2022, 39(6): 1896-1906.
  [Lu Yayan, Xu Xiaoliang, Li Jicai, et al. Research on the spatio-temporal variation of carbon storage in the Xinjiang Tianshan Mountains based on the InVEST model[J]. Aird Zone Research, 2022, 39(6): 1896-1906.]
[24] Tang Xuli, Zhao Xia, Bai Yongfei, et al. Carbon pools in China’s terrestrial ecosystems: New estimates based on an intensive field survey[J]. Proceedings of the National Academy of Sciences, 2018, 115(16): 4021-4026.
[25] Lai Li, Huang Xianjin, Yang Hong, et al. Carbon emissions from land-use change and management in China between 1990 and 2010[J]. Science Advances, 2016, 2(11): e1601063.
[26] Jiang Yefeng, Huang Mingxiang, Chen Xueyao, et al. Identification and risk prediction of potentially contaminated sites in the Yangtze River Delta[J]. The Science of The Total Environment, 2022, 815(51): 151982.
[27] Feng Dingrao, Bao Wenkai, Fu Meichen, et al. Current and future land use characters of a national central city in Eco-Fragile region: A case study in Xi’an city based on FLUS model[J]. Land, 2021, 10(3): 286.
[28] 王劲峰, 徐成东, 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1):116-134.
  [Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1):116-134.]
[29] 吕晨, 蓝修婷, 孙威. 地理探测器方法下北京市人口空间格局变化与自然因素的关系研究[J]. 自然资源学报, 2017, 32(8):1385-1397.
  [Lü Chen, Lan Xiuting, Sun Wei. A study on the relationship between natural factors and population distribution in Beijing using geographical detector[J]. Journal of Natural Resources, 2017, 32(8): 1385-1397.]
[30] 唐睿, 彭开丽. 土地利用变化对区域陆地碳储量的影响研究综述[J]. 江苏农业科学, 2018, 46(19): 5-11.
  [Tang Rui, Peng Kaili. Impact of land use change on regional land carbon storage: A review[J]. Jiangsu Agricultural, 2018, 46(19): 5-11.]
[31] 内蒙古自治区林业和草原局. 内蒙古黄河流域林草生态建设取得阶段性成果[J]. 内蒙古林业, 2022(4), 7-9.
  [Inner Mongolia Autonomous Region Forestry and Grassland Bureau. Progress in the ecological construction of forests and grasses in the Yellow River Basin of Inner Mongolia[J]. Journal of Inner Mongolia Forestry, 2022(4), 7-9.]
[32] Zheng Huiling, Zheng Huifeng. Assessment and prediction of carbon storage based on land use/land cover dynamics in the coastal area of Shandong Province[J]. Ecological Indicators, 2023, 153(23) : 110474.
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