耦合PLUS-InVEST模型的海南热带雨林国家公园碳储量时空演变与预测
作者:
中图分类号:

X87

基金项目:

国家林业和草原局西南调查规划院科技项目“海南热带雨林国家公园建设专题评估”(2023-166)


Spatial-temporal Evolution and Prediction of Carbon Storage in Hainan Tropical Rainforest National Park by Coupling PLUS-InVEST Models
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [33]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    [目的] 研究海南热带雨林国家公园在不同情景下的土地利用和碳储量变化,为优化该区土地利用格局,制定保护政策提供科学依据。[方法] 以2001,2011,2021海南热带雨林国家公园土地利用数据为基础,利用PLUS模型和InVEST模型相结合的方法,分析研究区在2001—2021年及2030年不同情景下的土地利用及碳储量变化。[结果] ①2001—2021年海南热带雨林国家公园土地利用变化的特征为耕地、草地、水域面积逐年减少,林地、人造地表面积不断扩张,20 a间林地面积增加561.19 km2;到2030年,自然发展与耕地保护情景下土地利用变化模拟结果有些相似,而在生态保护情景下,土地利用变化与其他两种情景截然相反。②2001,2011,2021年海南热带雨林国家公园碳储量分别为8.72×107 t,9.22×107 t,9.13×107 t,到2030年自然发展情景下碳储量为9.04×107 t,耕地保护情景下碳储量为9.12×107 t,生态保护情景下碳储量为9.13×107 t,说明实施生态保护措施可以进一步提升海南热带雨林国家公园固碳能力。[结论] 海南热带雨林国家公园碳储量变化与土地利用变化呈高度一致性,土地利用变化很大程度上决定了碳储总量及空间分布。

    Abstract:

    [Objective] The changes of land use and carbon storage under different scenarios were analyzed to provide the scientific bases were provided for optimizing of land use pattern and formulating protection policies in Hainan Tropical Rainforest National Park. [Methods] Based on the land use data of Hainan Tropical Rainforest National Park in 2001, 2011 and 2021, and the PLUS and InVEST models, the changes of land use and carbon storage in 2001—2021 and 2030 under different scenarios were analyzed and predicted, respectively. [Results] ① From 2001 to 2021, the cultivated lands, grassland and water decreased continually, while the forest land and construction land gradually expanded in Hainan Tropical Rainforest National Park. And the forest land increased by 561.19 km2 in 20 years. The predicting results of land use changes under natural development scenario and farmland protection scenario in 2030 were similar but were much different with the results of ecological protection scenario. ② In 2001, 2011, and 2021, the carbon storage of Hainan Tropical Rainforest National Park was 8.72×107 t,9.22×107 t,and 9.13×107 t, respectively. In 2030, the carbon storage of Hainan Tropical Rainforest National Park would be 9.04×107 t under natural development scenario, 9.12×107 t under farmland protection scenario, 9.13×107 t under ecological protection scenario. These results indicating that the ecological protection measures could improve the ability of carbon storage in Hainan Tropical Rainforest National Park. [Conclusion] The change of carbon storage was highly consistent with the change of land use, and land use change could affect the pattern of carbon storage in Hainan Tropical Rainforest National Park.

    参考文献
    [1] Costanza R, de Groot R, Sutton P, et al. Changes in the global value of ecosystem services [J]. Global Environmental Change, 2014,26:152-158.
    [2] 雒舒琪,胡晓萌,孙媛,等.耦合PLUS-InVEST模型的多情景土地利用变化及其对碳储量影响[J].中国生态农业学报(中英文),2023,31(2):300-314. Luo Shuqi, Hu Xiaomeng, Sun Yuan, et al. Multi-scenario land use change and its impact on carbon storage based on coupled Plus-Invest model [J]. Chinese Journal of Eco-Agriculture, 2023,31(2):300-314.
    [3] 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. Zhang Yan, Shi Xueyi, Tang Qian. Carbon storage assessment in the upper reaches of the Fenhe River under different land use scenarios [J]. Acta Ecologica Sinica, 2021,41(1):360-373.
    [4] 王方邑,赵智聪,王沛,等.中国自然保护地碳中和贡献的初步评估及三个关键研究课题[J].中国园林,2023,39(3):6-13. Wang Fangyi, Zhao Zhicong, Wang Pei, et al. The preliminary assessment and three key issues of carbon neutrality contribution of protected areas in China [J]. Chinese Landscape Architecture, 2023,39(3):6-13.
    [5] Maxwell S L, Cazalis V, Dudley N, et al. Area-based conservation in the twenty-first century [J]. Nature, 2020,586(7828):217-227.
    [6] 杨蕾,杨立,李婧昕,等.东北地区5个物种潜在栖息地变化与优化保护规划[J].生态学报,2019,39(3):1082-1094. Yang Lei, Yang Li, Li Jingxin, et al. Potential distribution and conservation priority areas of five species in Northeast China [J]. Acta Ecologica Sinica, 2019,39(3):1082-1094.
    [7] WWF International. Management Effectiveness Tracking Tool:Reporting Progress at Protected Area Sites:Second Edition[EB/OL].(2007-07)[2021-11-22]. https://wwfeu.awsassets.panda.org/downloads/mett2_final_version_july_2007.pdf.
    [8] GROSS, J E, WOODLEY S, WELLING L A. Adapting to Climate Change:Guidance for Protected Area Managers and Planners[M/OL]. Gland:IUCN,2016:xviii, 129. https://portals.iucn.org/library/sites/library/files/documents/PAG-024.pdf.
    [9] IUCN. Protected Areas and Climate Change[EB/OL].(2022-07-21)[2022-11-30]. https://www.iucn.org/sites/default/files/2022-7/protected_areas_and_climate_change_briefing_paper_december_2019-final.pdf.
    [10] 钟乐,赵智聪,王小珊,等.基于气候变化与生物多样性协同的中国自然保护地建设路径[J].风景园林,2022,29(6):56-62. Zhong Le, Zhao Zhicong, Wang Xiaoshan, et al. Construction path of protected areas in China based on the synergy of climate change response and biodiversity conservation [J]. Landscape Architecture, 2022,29(6):56-62.
    [11] 吴先雯,郭风成.基于Invest模型和Flus模型的江苏省碳储量变化模拟与预测[J].中国生态农业学报(中英文),2024,32(2):230-239. Wu Xianwen, Guo Fengcheng. Analysis and prediction of carbon storage changes in Jiangsu Province based on the Invest model and Flus model [J]. Chinese Journal of Eco-agriculture, 2024,32(2):230-239.
    [12] Wang Ziyao, Li Xin, Mao Yueting, et al. Dynamic simulation of land use change and assessment of carbon storage based on climate change scenarios at the city level: A case study of Bortala, China [J]. Ecological Indicators, 2022,134:108499.
    [13] 周汶颖.基于Logistic-CA-Markov和InVEST模型的上海市土地利用与碳储量时空演化及预测[D].上海:上海师范大学,2023. Zhou Wenying Analysis and prediction of land use and carbon storage in Shanghai based on the Logistic-CA-Markov model and InVEST model [D]. Shanghai: Shanghai Normal University, 2023.
    [14] 胥丽,罗绍龙,国朝胜,等.基于PLUS模型和InVEST模型的西双版纳碳储量变化研究[J].三峡生态环境监测,2023,8(2):75-87. Xu Li, Luo Shaolong, Guo Chaosheng, et al. Carbon storage change in Xishuangbanna based on PLUS and InVEST model [J]. Ecology and Environmental Monitoring of Three Gorges, 2023,8(2):75-87.
    [15] Liang Xun, Guan Qingfeng, 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, 2021,85:101569.
    [16] 尹珂,廖思雨.基于InVEST模型和Plus模型的三峡库区(重庆段)碳储量时间变化及预测[J/OL]. 长江科学院院报. https://link.cnki.net/urlid/42.1171.TV.20231229.1321.002. Yin Ke, Liao Siyu. Spatial and temporal variability and prediction of carbon stocks in the Three Gorges reservoir area (Chongqing section) based on the InVEST-PLUS model [J/OL]. Journal of Yangtze River Scientific Research Institute. https://link.cnki.net/urlid/42.1171.TV.20231229.1321.002.
    [17] 方赞山,钟才荣,王凤霞,等.耦合InVEST与FLUS模型的海南岛生态系统碳储量时空演变与预测[J].水土保持通报,2023,43(5):320-329. Fang Zanshan, Zhong Cairong, Wang Fengxia, et al. Spatial-temporal evolution and prediction of ecosystem carbon storage on Hainan Island by coupling InVEST and FLUS models [J]. Bulletin of Soil and Water Conservation, 2023,43(5):320-329.
    [18] 张育诚,韩念龙,胡珂,等.海南岛中部山区土地利用变化对碳储量时空分异的影响[J].南京林业大学学报(自然科学版),2023,47(2):115-122. Zhang Yucheng, Han Nianlong, Hu Ke, et al. The impact of land-use changes on the spatio-temporal variation of carbon storage in the central mountainous area of Hainan Island [J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 2023,47(2):115-122.
    [19] 刘强,周璋,陈德祥,等.海南热带雨林国家公园森林生态系统碳储量及变化特征[J].自然保护地,2023,3(4):1-10. Liu Qiang, Zhou Zhang, Chen Dexiang, et al. Carbon storage and its change characteristics of forest ecosystems in National Park of Hainan tropical rainforest, China [J]. Natural Protected Areas, 2023,3(4):1-10.
    [20] 吴慧.海南岛热带雨林西部天然林土壤有机碳分布特征及其影响因素研究[D].海南海口:海南师范大学,2023. Wu Hui Distribution characteristics and influencing factorsof soil organic carbon in natural forests in the westerntropical rainforest of Hainan Island [D]. Haikou, Hainan: Hainan Normal University, 2023.
    [21] 吴庭天,陈毅青,陈宗铸,等.海南热带雨林代表性种群空间分布特征研究[J].林草资源研究,2023(5):133-141. Wu Tingtian, Chen Yiqing, Chen Zongzhu, et al. Analysis on the spatial distribution characteristics of representative populations in tropical rainforest of Hainan [J]. Forest and Grassland Resources Research, 2023(5):133-141.
    [22] 黄韬,刘素红.基于PLUS-InVEST模型的福建省土地利用变化与碳储量评估[J].水土保持学报,2024,38(2):246-257. Huang Tao, Liu Suhong. Evaluation of land use change and carbon storage in Fujian Province based on PLUS-InVEST model [J]. Journal of Soil and Water Conservation, 2024,38(2):246-257.
    [23] 杨朔,苏昊,赵国平.基于PLUS模型的城市生态系统服务价值多情景模拟: 以汉中市为例[J].干旱区资源与环境,2022,36(10):86-95. Yang Shuo, Su Hao, Zhao Guoping. Multi-scenario simulation of urban ecosystem service value based on PLUS model: A case study of Hanzhong City [J]. Journal of Arid Land Resources and Environment, 2022,36(10):86-95.
    [24] 李俊,杨德宏,吴锋振,等.基于PLUS与InVEST模型的昆明市土地利用变化动态模拟与碳储量评估[J].水土保持通报,2023,43(1):378-387. Li Jun, Yang Dehong, Wu Fengzhen, et al. Dynamic simulation of land use changes and assessment of carbon storage in Kunming City based on PLUS and InVEST models [J]. Bulletin of Soil and Water Conservation, 2023,43(1):378-387.
    [25] Zhang Fan, Zhan Jinyan, Zhang Qian, et al. Impacts of land use/cover change on terrestrial carbon stocks in Uganda [J]. Physics and Chemistry of the Earth, Parts A/B/C, 2017,101:195-203.
    [26] 段璇瑜,龚文峰,孙雨欣,等.海南岛海岸带土地利用变化及其对碳储量时空演变的影响[J].水土保持通报,2022,42(5):301-311. Duan Xuanyu, Gong Wenfeng, Sun Yuxin, et al. Land use change and its impact on temporal and spatial evolution of carbon storage in coastal zone of Hainan Island [J]. Bulletin of Soil and Water Conservation, 2022,42(5):301-311.
    [27] 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.
    [28] 段璇瑜.海南岛海岸带土地利用/覆盖变化及其对碳储量影响的评估预测[D].海南海口:海南大学,2023. Duan Xuanyu, Land use/cover change and its impact on carbon storage in Hainan Island coastal zone [D]. Haikou, Hainan: Hainan University, 2023.
    [29] 傅楷翔,贾国栋,余新晓,等.耦合PLUS-InVEST-Geodector模型的新疆地区碳储量时空变化及驱动机制分析[J/OL].环境科学. https://doi.org/10.13227/j.hjkx.202309230. FU Kaixiang, JIA Guodong, YU Xinxiao, et al. Analysis of Temporal and Spatial Carbon Stock Changes and Driving Mechanism in Xinjiang Region by Coupled PLUS-InVEST-Geodector Model[J/OL]. Environmental Science. https://doi.org/10.13227/j.hjkx.202309230.
    [30] 陈竹安,柳雪.基于InVEST-PLUS模型的碳储量时空变化与多情景模拟预测: 以江西省为例[J].上海国土资源,2023,44(4):146-153. Chen Zhu’an, Liu Xue. Spatio-temporal variation and multi-scenario prediction of carbon storage based on the InVEST-PLUS model: A case study of Jiangxi Province [J]. Shanghai Land & Resources, 2023,44(4):146-153.
    [31] 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. Ecosystem carbon storage in Hangzhou Bay area based on InVEST and PLUS models [J]. Environmental Science, 2023,44(6):3343-3352.
    [32] 王子昊,王冰,张宇飞,等.基于PLUS-InVEST模型的呼和浩特多情影土地利用变化动态模拟及碳储量评估[J/OL].农业资源与环境学报. https://doi.org/10.13254/j.jare.2023.0249. Wang Zihao, Wang Bing, Zhang Yufei, et al. Dynamic simulation of multi-scenario land use change and carbon storage assessment in Hohhot City based on PLUS-InVEST model [J/OL]. Journal of Agricultural Resources and Environment. https://doi.org/10.13254/j.jare.2023.0249.
    [33] 何磊,叶思源,赵广明,等.海岸带滨海湿地蓝碳管理的研究进展[J].中国地质,2023,50(3):777-794. He Lei, Ye Siyuan, Zhao Guangming, et al. Research progress on blue carbon management in coastal wetland ecotones [J]. Geology in China, 2023,50(3):777-794.
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

肖义发.耦合PLUS-InVEST模型的海南热带雨林国家公园碳储量时空演变与预测[J].水土保持通报,2024,43(5):305-314

复制
分享
文章指标
  • 点击次数:39
  • 下载次数: 128
  • HTML阅读次数: 82
  • 引用次数: 0
历史
  • 收稿日期:2024-03-06
  • 最后修改日期:2024-05-07
  • 在线发布日期: 2024-11-02