基于土地变化的贵州省碳储量演变及其脆弱性特征分析
作者:
作者单位:

1.贵州师范大学 地理与环境科学学院, 贵州 贵阳 550025;2.北京师范大学 水科学研究院, 北京 100000;3.贵州省生态气象和卫星遥感中心, 贵州 贵阳 550002

通讯作者:

周旭(1981-), 男(汉族), 四川省古蔺县人, 博士, 副教授, 主要从事遥感水文与流域管理研究。Email: zxzy8178@163.com

中图分类号:

P96, X87

基金项目:

国家自然科学基金委员会—贵州省人民政府喀斯特科学研究中心项目“喀斯特生物多样性形成和维持的钙依赖机制及其应用基础”(U1812401);贵州省科学技术项目([2017]1131);贵州省科技支撑项目([2017]2855)


Analysis of Carbon Stock Evolution and Its Vulnerability Characteristics Based on Land Use Change in Guizhou Province
Author:
Affiliation:

1.School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang, Guizhou 550025, China;2.Institute of Water Science, Beijing Normal University, Beijing 100000, China;3.Ecological Meteorology and Satellite Remote Sensing Center of Guizhou Province, Guiyang, Guizhou 550002, China

Fund Project:

Analysis of Carbon Stock Evolution and Its Vulnerability Characteristics Based on Land Use Change in Guizhou Province

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    摘要:

    目的 分析贵州省生态系统碳储量时空分布格局、演变特征及其对土地利用转移的响应,研究各县域生态系统碳储量服务的脆弱性,为贵州省区域土地利用管理决策及“双碳”目标的实现提供科学依据和参考。 方法 运用InVEST模型和潜在影响指数(PI)分析贵州省2000—2020年碳储量变化特征和生态系统碳储存服务的脆弱性。 结果 ① 近20 a间贵州省土地利用结构发生显著变化,前10 a和后10 a分别有14.10%,17.29%的土地发生转移,耕地是建设用地扩张的主要来源。②贵州省20 a间生态系统碳储量减少2.40×107 t,林地的缩减和建设用地的扩张是碳储量减少的主要原因。③贵州省碳储量Moran's I指数均大于0,空间分布具有显著的空间正相关性和集聚性。冷热点分析显示碳储量热点分布较为分散,冷点分布集中稳定。④贵州省前10 a和后10 a PI指数分别为-1.27和-0.15,脆弱性有所改善。县域间脆弱性存在空间差异,边缘县域负向影响显著,20 a间81.82%的县脆弱性降低。 结论 贵州省林地的转出和建设用地的扩张对碳储量和碳储量服务脆弱性影响显著,未来应优化土地利用结构,加强规划管理。

    Abstract:

    Objective The spatial and temporal distribution pattern and evolution characteristics of ecosystem carbon storage, its response to land use change, and the vulnerability of ecosystem carbon storage service in each county of Guizhou Province were analyzed in order to provide a scientific basis and reference for regional land use management decision-making and to realize the "dual carbon" goal. Methods The InVEST model and the potential impact (PI) index were used to analyze the characteristics of carbon stock changes and the vulnerability of ecosystem carbon storage services in Guizhou Province from 2000 to 2020. Results ① Land use type in Guizhou Province changed significantly during the last 20 years. 14.10% and 17.29% of the land changed type in the first 10 years and the last 10 years, respectively. Cultivated land was the main source of construction land expansion. ② Ecosystem carbon storage in Guizhou Province decreased by 0.24 billion tons in the past 20 years. Forest land reductions and construction land expansion were the main reasons for carbon storage reduction. ③ All Moran's I indices of ecosystem carbon stocks in Guizhou Province exceeded 0, indicating significant positive spatial correlation and agglomeration. The hot spot/cold-spot analysis showed that the distribution of carbon stock hot spots was relatively decentralized while the distribution of cold spots was centralized and stable. ④ The PI indices for Guizhou Province in the first and second 10-year periods were -1.27 and -0.15, respectively, indicating an improvement in vulnerability. There were spatial differences in vulnerability among counties, with significant negative effects in the peripheral counties. The vulnerability of 81.82% of the counties decreased in 20 years. Conclusion The transfer of forest land and the expansion of construction land in Guizhou Province had a significant impact on carbon stocks and the vulnerability of carbon stock services. In the future, land use structure should be optimized, and planning and management should be strengthened.

    参考文献
    [1] Lu Fei, Hu Huifeng, Sun Wenjuan, et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010[J]. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115(16): 4039-4044.
    [2] Watson R T, Change I P O C. Land use, land-use change, and forestry: A special report of the IPCC[M]. Cambridge: Cambridge University Press, 2000.
    [3] Batjes N H. Total carbon and nitrogen in the soils of the world[J]. European Journal of Soil Science, 2014, 65(1): 10-21.
    [4] 陈广生, 田汉勤. 土地利用/覆盖变化对陆地生态系统碳循环的影响[J]. 植物生态学报, 2007, 31(2): 189-204.
    [5] Zhang Mei, Huang Xianjin, Chuai Xiaowei, et al. Impact of land use type conversion on carbon storage in terrestrial ecosystems of China: A spatial-temporal perspective[J]. Scientific Reports, 2015, 5: 10233.
    [6] Kondo M, Ichii K, Patra P K, et al. Land use change and El Ni?o-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia[J]. Nature Communications, 2018, 9(1): 1154.
    [7] 柳嘉佳, 王普昶, 王志伟, 等. 基于InVEST模型的贵州喀斯特生态系统服务功能评估研究进展[J]. 安徽农业科学, 2021, 49(20): 25-27.
    [8] 王天福, 龚直文, 邓元杰. 基于土地利用变化的陕西省植被碳汇提质增效优先区识别[J]. 自然资源学报, 2022, 37(5): 1214-1232.
    [9] 虎帅, 张学儒, 官冬杰. 基于InVEST模型重庆市建设用地扩张的碳储量变化分析[J]. 水土保持研究, 2018, 25(3): 323-331.
    [10] Zhu Guofeng, et al. Land-use changes lead to a decrease in carbon storage in arid region, China[J]. Ecological Indicators, 2021, 127: 107770.
    [11] 张燕, 师学义, 唐倩. 不同土地利用情景下汾河上游地区碳储量评估[J]. 生态学报, 2021, 41(1): 360-373.
    [12] 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 International, 2022, 29(30): 45507-45526.
    [13] Li Jingye, Gong Jian, Guldmann J M, et al. Carbon dynamics in the Northeastern Qinghai-Tibetan Plateau from 1990 to 2030 using land sat land use/cover change data[J]. Remote Sensing, 2020, 12(3): 528.
    [14] 丁访军, 高艳平, 周凤娇, 等. 贵州西部4种林型土壤有机碳及其剖面分布特征[J]. 生态环境学报, 2012, 21(1): 38-43.
    [15] 惠辽辽, 邵景安, 慈恩, 等. 近30 a贵州遵义县农田土壤有机碳动态及影响因素分析[J]. 自然资源学报, 2014, 29(4): 653-665.
    [16] 陈美景, 王庆日, 白中科, 等. 碳中和愿景下"三生空间"转型及其碳储量效应: 以贵州省为例[J]. 中国土地科学, 2021, 35(11): 101-111.
    [17] 刘金龙, 马程, 王阳, 等. 基于径向基函数网络的京津冀地区生态系统服务脆弱性评估[J]. 北京大学学报(自然科学版), 2013, 49(6): 1040-1046.
    [18] 黄静, 崔胜辉, 李方一, 等. 厦门市土地利用变化下的生态敏感性[J]. 生态学报, 2011, 31(24): 7441-7449.
    [19] Chen Jun, Chen Jin, Liao Anping, et al. Global land cover mapping at 30 m resolution: A POK-based operational approach[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 103: 7-27.
    [20] Yang Yongke. Accuracy assessment of seven global land cover datasets over China[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 125: 156-173.
    [21] 陈光水, 杨玉盛, 谢锦升, 等. 中国森林的地下碳分配[J]. 生态学报, 2007, 27(12): 5148-5157.
    [22] Giardina C P, Ryan M G. Evidence that decomposition rates of organic carbon in mineral soil do not vary with temperature[J]. Nature, 2000, 404(6780): 858-861.
    [23] Alam S A. Tree biomass and soil organic carbon densities across the Sudanese woodland savannah: A regional carbon sequestration study[J]. Journal of Arid Environments, 2013, 89: 67-76.
    [24] Chuai Xiaowei, Huang Xianjin, Lai Li, et al. Land use structure optimization based on carbon storage in several regional terrestrial ecosystems across China[J]. Environmental Science & Policy, 2013, 25: 50-61.
    [25] 丁访军, 潘忠松, 吴鹏, 等. 贵州东部常绿落叶阔叶混交林碳素积累及其分配特征[J]. 生态学报, 2015, 35(6): 1761-1768.
    [26] 李义平, 蔡宏, 田鹏举, 等. 贵州省黎平县地表覆被变化引起的生态系统碳储量变化[J]. 水土保持通报, 2020, 40(2): 92-99.
    [27] 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.
    [28] McCarthy J J, Canziani O F, Leary N A, et al. IPCC. 2001: Climate change 2001: impacts, adaptation and vulnerability, Contribution of Working Group Ⅱ to the third assessment report of the intergovernmental panel on climate change[J]. International Journal of Climatology, 2002, 22(10): 1285-1285.
    [29] Schröter D, Cramer W, Leemans R, et al. Ecosystem service supply and vulnerability to global change in Europe[J]. Science, 2005, 310(5752): 1333-1337.
    [30] Metzger M J. The vulnerability of ecosystem services to land use change[J]. Agriculture, Ecosystems & Environment, 2006, 114(1): 69-85.
    [31] 汪瑞, 何如海, 栾倩, 等. 滁州市陆地生态系统土壤碳储量对土地利用变化响应[J]. 国土与自然资源研究, 2015(3): 7-11.
    [32] 庄大方, 刘纪远. 中国土地利用程度的区域分异模型研究[J]. 自然资源学报, 1997, 12(2): 105-111.
    [33] 张继, 周旭, 蒋啸, 等. 生态工程建设背景下贵州高原的植被变化及影响因素分析[J]. 长江流域资源与环境, 2019, 28(7): 1623-1633.
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陈大蓉,周旭,杨胜天,裴宇,胡玉雪,胡锋.基于土地变化的贵州省碳储量演变及其脆弱性特征分析[J].水土保持通报,2023,43(3):301-309

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  • 收稿日期:2022-08-26
  • 最后修改日期:2022-10-08
  • 在线发布日期: 2023-09-28