Spatial-temporal evolution and prediction of carbon storage in Mohe city by linking the logistic-CA-Markov and InVEST models

被引:1
作者
Yan, Xuan [1 ,2 ]
Li, Miao [1 ,2 ]
Guo, Dianfan [1 ,2 ]
Yang, Dongyu [1 ,2 ]
Zhan, Daqing [1 ,2 ]
机构
[1] Harbin Normal Univ, Coll Geog Sci, Harbin, Peoples R China
[2] Heilongjiang Prov Key Lab Geog Environm Monitoring, Harbin, Peoples R China
基金
中国国家自然科学基金;
关键词
LUCC; carbon storage; logistic-CA-Markov model; InVEST model; optimal parameters-based geographical Detector; spatial autocorrelation analysis; LAND-USE; TERRESTRIAL ECOSYSTEMS; ORGANIC-CARBON; DYNAMICS; BIOMASS; REGION; SOIL;
D O I
10.3389/feart.2024.1383237
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Carbon storage plays a vital role in the provision of ecosystem services, and the alteration of land use has a profound influence on the carbon storage capacity of ecosystems. Therefore, in this study, two scenarios of natural evolution scenario (NES) and ecological conservation scenario (ECS) were set up based on the development of Mohe City,China. Meanwhile, a coupled model of LUCC and ecosystem carbon storage was established using Logistic-CA-Markov and InVEST models, as well as optimal parameters_based geographical Detector and GeoDa, to predict the distribution and change of ecosystem carbon storage based on LUCC in the future. The effects of different influencing factors on the spatial differentiation of carbon storage were also explored. The results show that: (1) From 1980 to 2020, the land use type in Mohe City was dominated by the forest and its area decreased; the area of wetland increased. From 2020 to 2040, ecological benefits will be shown under the ECS, with an increase in forest and a slower expansion of built-up. (2) Carbon loss in Mohe City from 1980 to 2020 was 4.04Tg. Under the ECS carbon storage increased slightly by 0.2Tg. Soil carbon storage was the main carbon pool in Mohe City, and forest was the largest contributor. The carbon storage of Mohe city in 2030 and 2040 has a strong positive spatial correlation. Hot spots in more than a cold spots area, the high value area is concentrated in the east, low concentrated in urban areas. (3) Apart from LUCC, mean annual precipitation was the most significant factors affecting the spatial differentiation variability of carbon storage. The interactions of mean annual precipitation and population density with other factors exhibit a non-linear enhancement,which had a coefficient of 21.91%. This study contributes to a deeper understanding of the relationship between LUCC and carbon storage.
引用
收藏
页数:19
相关论文
共 66 条
  • [1] Tree biomass and soil organic carbon densities across the Sudanese woodland savannah: A regional carbon sequestration study
    Alam, S. A.
    Starr, M.
    Clark, B. J. F.
    [J]. JOURNAL OF ARID ENVIRONMENTS, 2013, 89 : 67 - 76
  • [2] [Anonymous], 1982, J. Glaciol. Geocryol.
  • [3] Bai Edith, 2020, Chinese Journal of Plant Ecology, V44, P543, DOI 10.17521/cjpe.2020.0071
  • [4] Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale
    Basse, Reine Maria
    Omrani, Hichem
    Charif, Omar
    Gerber, Philippe
    Bodis, Katalin
    [J]. APPLIED GEOGRAPHY, 2014, 53 : 160 - 171
  • [5] Carbon emissions from agricultural expansion and intensification in the Chaco
    Baumann, Matthias
    Gasparri, Ignacio
    Piquer-Rodrguez, Mara
    Gavier Pizarro, Gregorio
    Griffiths, Patrick
    Hostert, Patrick
    Kuemmerle, Tobias
    [J]. GLOBAL CHANGE BIOLOGY, 2017, 23 (05) : 1902 - 1916
  • [6] Chen S., 2007, J. Subtrop. Resour. Environ, V2, P34, DOI DOI 10.19687/J.CNKI.1673-7105.2007.01.005
  • [7] [陈耀亮 CHEN Yaoliang], 2015, [自然资源学报, Journal of Natural Resources], V30, P397
  • [8] Chen Z., 2022, Sci. Technol. Eng, V22, P3387
  • [9] Cheng R. B., 2021, Univ. Chengdu Technol, DOI [10.26986/d.cnki.gcdlc.2021.000561, DOI 10.26986/D.CNKI.GCDLC.2021.000561]
  • [10] Deng Yuan-jie, 2022, Journal of Nanjing Forestry University (Natural Sciences Edition), V46, P106