Spatial-temporal variation of ecosystem carbon storage driven by land use in northwest inland desert resource region in recent 30 years

FU Yujia; LIU Xiaohuang; SUN Xingli; LIU Jiufen; ZHENG Yiwen; ZHANG Zifan; LAI Ming; XIONG Maoqiu

doi:10.12097/gbc.2022.07.023

2024 Vol. 43, No. 2~3

Article Contents

Article navigation > Geological Bulletin of China > 2024 > 43(2~3): 451-462

Next Article Previous Article

FU Yujia, LIU Xiaohuang, SUN Xingli, LIU Jiufen, ZHENG Yiwen, ZHANG Zifan, LAI Ming, XIONG Maoqiu. 2024. Spatial-temporal variation of ecosystem carbon storage driven by land use in northwest inland desert resource region in recent 30 years. Geological Bulletin of China, 43(2~3): 451-462. doi: 10.12097/gbc.2022.07.023

Citation:

FU Yujia, LIU Xiaohuang, SUN Xingli, LIU Jiufen, ZHENG Yiwen, ZHANG Zifan, LAI Ming, XIONG Maoqiu. 2024. Spatial-temporal variation of ecosystem carbon storage driven by land use in northwest inland desert resource region in recent 30 years. Geological Bulletin of China, 43(2~3): 451-462. doi: 10.12097/gbc.2022.07.023

Spatial-temporal variation of ecosystem carbon storage driven by land use in northwest inland desert resource region in recent 30 years

1.
School of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan 430074, Hubei, China
2.
Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China
3.
Hebei GEO University, Shijiazhuang 050031, Hebei, China
4.
Institute of Geological Survey, China University of Geosciences (Wuhan), Wuhan 430074, Hubei, China
5.
School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, Hubei, China
6.
School of Earth Resources, China University of Geosciences (Wuhan), Wuhan 430074, Hubei, China

More Information

Corresponding author: LIU Xiaohuang, liuxh19972004@163.com

Received Date: 23 July 2022

Revised Date: 06 February 2023

Publish Date: 15 March 2024

Abstract

Abstract

Based on remote sensing images, elevation models, vegetation and meteorological data from 1990 to 2020, the comprehensive regionalization of natural resources in northwest inland desert resource region was obtained by means of regionalization analysis combining quantitative calculation and qualitative analysis. According to the climate factors in the northwest inland desert resource region, the carbon density of different land types under the national level was revised to obtain the carbon density data of the western arid region. Based on the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, we analyzed the effects of land use change on carbon stocks from 1990 to 2020. The results showed that :① In recent 30 years, the grassland in this study area was mainly degraded, and the grassland was mainly transformed into cultivated land and desert, and the land use type changed significantly from 2010 to 2020.② The spatial distribution of carbon storage in the study area is more in the west and less in the east. The grassland in Altai and Tacheng basin temperate grassland subregion and Yili Basin temperate grassland subregion are rich, so the carbon storage content is high.③ From 1990 to 2020, the carbon storage in the northwest inland desert resource region showed a decreasing trend. The conversion of land use type resulted a net reduction of carbon storage of 1.86×10⁸ tons. In 2000 and 2020, a large amount of grassland in the study area was transformed into desert, which significantly reduced soil carbon storage and carbon sequestration potential. This study evaluated the temporal and spatial changes of ecosystem carbon storage by land use in the northwest inland desert resource region, which is helpful to judge the transformation trend of ecosystem function and provide reference for ecosystem regulation and promoting low-carbon sustainable development in this region.
- land use change /
- ecosystem carbon storage /
- InVEST model /
- Northwest China

FullText(HTML)

References

[1]	Houghton R A, Nassikas A A. 2017. Global and regional fluxes of carbon from land use and land cover change 1850 —2015[J]. Global Biogeochemical Cycles, 3(31): 456−472. Google Scholar
[2]	Kalantaria Z, Ferreirab C S S, Pagea J, et al. 2019, Meeting sustainable development challenges in growing cities: Coupled social−ecological systems modeling of land use and water changes[J]. Journal of Environmental Management, 1(245): 471−480. Google Scholar
[3]	Liu G, Wei M, Yang Z, et al. 2023. Relationship between spatio−temporal evolution of soil pH and geological environment/surface cover in the eastern Nenjiang River Basin of Northeast China during the past 30 years[J]. China Geology, 6(3): 369−382. Google Scholar
[4]	Potter C S, Randerson J T, Field C B, et al. 1993. Terrestrial ecosystem production: A process model based on global Satellite and suface data[J]. Global Biogeochemical Cycles, 7(4): 811−841. Google Scholar
[5]	Tang X, Zhao X, Bai Y, et al. 2018. Carbon pools in China’s terrestrial ecosystems: New estimates based on an intensive field survey[J]. Proceedings of the National Academy of Sciences of the United States of America, 16(115): 4021−4026. Google Scholar
[6]	Zhou J, Zhao Y, Huang P, et al. 2020. Impacts of ecological restoration projects on the ecosystem carbon storage of inland river ba sin in arid area, China[J]. Ecological Indicators, (118): 106803. Google Scholar
[7]	Zhu G, Qiu D, Zhang Z, et al. 2021. Land−use changes lead to a decrease in carbon storage in arid region, China[J]. Ecological Indicators, (127): 107770. Google Scholar
[8]	阿米娜木·艾力, 常顺利, 张毓涛, 等. 2014. 天山云杉森林土壤有机碳沿海拔的分布规律及其影响因素[J]. 生态学报, 34(7): 1626−1634. Google Scholar
[9]	陈光水, 杨玉盛, 刘乐中, 等. 2007. 森林地下碳分配(TBCA)研究进展[J]. 亚热带资源与环境学报, (1): 34−42. doi: 10.3969/j.issn.1673-7105.2007.01.005 CrossRef Google Scholar
[10]	陈宁, 辛存林, 唐道斌, 等. 2023. 中国西北地区多情景土地利用优化与碳储量评估[J]. 环境科学, 44(8): 4655−4665. Google Scholar
[11]	揣小伟, 黄贤金, 郑泽庆, 等. 2011. 江苏省土地利用变化对陆地生态系统碳储量的影响[J]. 资源科学, 33(10): 1932−1939. Google Scholar
[12]	冯益明, 姚爱冬, 姜丽娜. 2014. CASA模型的改进及在干旱区生态系统NPP估算中的应用[J]. 干旱区资源与环境, 28(8): 39−43. Google Scholar
[13]	高扬, 何念鹏, 汪亚峰. 2013. 生态系统固碳特征及其研究进展[J]. 自然资源学报, 28(7): 1264−1274. doi: 10.11849/zrzyxb.2013.07.018 CrossRef Google Scholar
[14]	葛全胜, 戴君虎, 何凡能, 等. 2008. 过去300年中国土地利用、土地覆被变化与碳循环研究[J]. 中国科学(D辑), (2): 197−210. Google Scholar
[15]	黄卉. 2015. 基于InVEST模型的土地利用变化与碳储量研究[D]. 中国地质大学(北京)硕士学位论文. Google Scholar
[16]	黄莉, 刘晓煌, 刘玖芬, 等. 2021. 长时间尺度下自然资源动态综合区划理论与实践研究——以青藏高原为例[J]. 中国地质调查, 8(2): 109−117. Google Scholar
[17]	赖明, 吴淑玉, 张海燕, 等. 2021. 基于综合区划的中国西南地区自然资源动态变化特征分析[J]. 中国地质调查, 8(2): 83−91. Google Scholar
[18]	李传华, 曹红娟, 范也平, 等. 2019. 基于校正的CASA模型NPP遥感估算及分析——以河西走廊为例[J]. 生态学报, 39(5): 1616−1626. Google Scholar
[19]	李勇, 高岚. 2021. 中国“碳中和”目标的实现路径与模式选择[J]. 华南农业大学学报(社会科学版), 20(5): 77−93. Google Scholar
[20]	廖艳, 崔军, 杨忠芳, 等. 2012. 三江平原典型土地利用类型土壤呼吸强度对温度的敏感性[J]. 地质通报, 31(1): 164−171. doi: 10.3969/j.issn.1671-2552.2012.01.021 CrossRef Google Scholar
[21]	刘国华, 傅伯杰, 方精云. 2000. 中国森林碳动态及其对全球碳平衡的贡献[J]. 生态学报, (5): 733−740. doi: 10.3321/j.issn:1000-0933.2000.05.004 CrossRef Google Scholar
[22]	刘海霞, 马立志. 2016. 西北地区生态环境问题及其治理路径[J]. 实事求是, (4): 50−54. doi: 10.3969/j.issn.1003-4641.2016.04.10 CrossRef Google Scholar
[23]	刘建泉, 李进军, 郝虎, 等. 2017. 祁连山青海云杉林生物量与碳储量及其影响因素分析[J]. 现代农业科技, (12): 140−143. doi: 10.3969/j.issn.1007-5739.2017.12.088 CrossRef Google Scholar
[24]	刘晓娟, 黎夏, 梁迅, 等. 2019. 基于FLUS−InVEST模型的中国未来土地利用变化及其对碳储量影响的模拟[J]. 热带地理, 39(3): 397−409. Google Scholar
[25]	柳梅英, 包安明, 陈曦, 等. 2010. 近30年玛纳斯河流域土地利用/覆被变化对植被碳储量的影响[J]. 自然资源学报, 25(6): 926−938. doi: 10.11849/zrzyxb.2010.06.005 CrossRef Google Scholar
[26]	卢雅焱, 徐晓亮, 李基才, 等. 2022. 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, 39(6): 1896−1906. Google Scholar
[27]	马晓哲, 王铮. 2015. 土地利用变化对区域碳源汇的影响研究进展[J]. 生态学报, 35(17): 5898−5907. Google Scholar
[28]	曲福田, 卢娜, 冯淑怡. 2011. 土地利用变化对碳排放的影响[J]. 中国人口·资源与环境, 21(10): 76−83. doi: 10.3969/j.issn.1002-2104.2011.10.012 CrossRef Google Scholar
[29]	石聪. 2012. 徐州侧柏人工林生态系统碳储量影响因素研究[D]. 南京林业大学硕士学位论文. Google Scholar
[30]	宋佳颖. 2021. 西北五省植被NDVI的时空变化及驱动力研究[D]. 西北师范大学硕士学位论文. Google Scholar
[31]	王绍强, 周成虎, 李克让, 等. 2000. 中国土壤有机碳库及空间分布特征分析[J]. 地理学报, (5): 533−544. doi: 10.11821/xb200005003 CrossRef Google Scholar
[32]	王文俊. 2019. 福建省土壤有机碳储量估算、时空分布特征及其影响因素[J]. 现代地质, 33(6): 1295−1305. Google Scholar
[33]	王效科, 冯宗炜, 欧阳志云. 2001. 中国森林生态系统的植物碳储量和碳密度研究[J]. 应用生态学报, (1): 13−16. doi: 10.3321/j.issn:1001-9332.2001.01.003 CrossRef Google Scholar
[34]	王秀兰, 包玉海. 1999. 土地利用动态变化研究方法探讨[J]. 地理科学进展, (1): 83−89. Google Scholar
[35]	谢立军, 白中科, 杨博宇, 等. 2023. 碳中和背景下国内外陆地生态系统碳汇评估方法研究进展[J]. 地学前缘, 30(2): 447−462. Google Scholar
[36]	辛晓平, 丁蕾, 程伟, 等. 2020. 北方草地及农牧交错区草地植被碳储量及其影响因素[J]. 中国农业科学, 53(13): 2757−2768. doi: 10.3864/j.issn.0578-1752.2020.13.022 CrossRef Google Scholar
[37]	徐丽, 何念鹏, 于贵瑞. 2019. 2010s中国陆地生态系统碳密度数据集[J]. 中国科学数据(中英文网络版), 4(1): 90−96. Google Scholar
[38]	杨园园, 戴尔阜, 付华. 2012. 基于InVEST模型的生态系统服务功能价值评估研究框架[J]. 首都师范大学学报(自然科学版), 33(3): 41−47. Google Scholar
[39]	翟羽娟, 张艳红, 姜琦刚, 等. 2022. 吉林省西部农牧交错区“三生空间”时空演变[J]. 吉林大学学报(地球科学版), 52(3): 1016−1026. Google Scholar
[40]	张楚强, 向洋, 方婷, 等. 2022. LUCC影响下太原市生态系统碳储量时空变化及预测[J]. 安全与环境工程, 29(6): 248−258. Google Scholar
[41]	张峰, 周广胜, 王玉辉. 2008. 基于CASA模型的内蒙古典型草原植被净初级生产力动态模拟[J]. 植物生态学报, (4): 786−797. doi: 10.3773/j.issn.1005-264x.2008.04.007 CrossRef Google Scholar
[42]	张海燕, 樊江文, 黄麟, 等. 2020. 中国自然资源综合区划理论研究与技术方案[J]. 资源科学, 42(10): 1870−1882. Google Scholar
[43]	张杰, 李敏, 敖子强, 等. 2018. 中国西部干旱区土壤有机碳储量估算[J]. 干旱区资源与环境, 32(9): 132−137. Google Scholar
[44]	张子凡, 张海燕, 刘晓煌, 等. 2021. 华北地区自然资源综合区划的动态变化特征[J]. 中国地质调查, 8(2): 92−99. Google Scholar
[45]	郑艺文, 张海燕, 刘晓洁, 等. 2021. 1990—2018年东北地区综合区划下自然资源动态变化特征分析[J]. 中国地质调查, 8(2): 100−108. Google Scholar
[46]	周涛, 史培军. 2006. 土地利用变化对中国土壤碳储量变化的间接影响[J]. 地球科学进展, (2): 138−143. doi: 10.3321/j.issn:1001-8166.2006.02.004 CrossRef Google Scholar