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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
引用本文:刘晓娟,黎夏,梁迅,石洪,欧金沛.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,2019,39(3):397-409.
作者姓名:刘晓娟  黎夏  梁迅  石洪  欧金沛
作者单位:(1. 中山大学地理科学与规划学院,广东省城市化与地理环境空间模拟重点实验室,广州510275; 2. 华东师范大学地理科学学院,地理信息科学教育部重点实验室,上海 200241)
基金项目:国家重点研发计划(2017YFA06044002);国家自然科学基金(41531176、41801304)
摘    要:基于代表性浓度路径情景(Representative Concentration Pathways, RCPs),耦合FLUS-InVEST(Future Land Use Simulation-Integrated Valuation of Ecosystem Services and Trade-offs, FLUS-InVEST)模型,以土地利用视角模拟了中国2100年的陆地生态系统碳储量,探讨其空间分异。结果表明:1)历史土地利用变化作用下,中国生态系统碳储量减少中心由华北地区转向东北地区,增加中心由西北地区转向西南地区;碳储量的减少由林地生态系统转向草地生态系统。2)未来RCPs情景下,中国林地生态系统碳储量都将持续增加,草地生态系统碳储量持续减少。RCP 6.0情景下,中国林地面积将增加9.43%左右,草地面积减少5.42%,全国林地碳储量较2010年增加2 332.64 Tg,而草地碳储量将损失1 719.03 Tg。在RCP 8.5情景下,全国林地面积增加5.15%,草地面积将减少5.10%,林地碳储量较2010年将增加1 754.59 Tg,草地碳储量将损失2 468.80 Tg。3)RCP 6.0情景对未来碳汇贡献度较RCP 8.5情景大。在RCP 6.0情景下,植被地上碳储量和表层土壤碳储量分别净增加127.12和83.67 Tg。但在RCP 8.5情景下,植被地上碳储量和表层土壤碳储量分别净减少24.67和32.41 Tg。4)不同RCPs情景下,碳储量增长均集中在横断山-秦岭-太行山-大兴安岭和雪峰山-太行山-大兴安岭两带;减少区域主要分布于云贵高原、四川盆地和京津冀地区。

关 键 词:土地利用变化  FLUS-InVEST模型  代表性浓度路径情景  生态系统碳储量  中国  
收稿时间:2019-02-19

Simulating the Change of Terrestrial Carbon Storage in China Based on the FLUS-InVEST Model
Liu Xiaojuan,Li Xia,Liang Xun,Shi Hong and Ou Jinpei.Simulating the Change of Terrestrial Carbon Storage in China Based on the FLUS-InVEST Model[J].Tropical Geography,2019,39(3):397-409.
Authors:Liu Xiaojuan  Li Xia  Liang Xun  Shi Hong and Ou Jinpei
Institution:[1. School of Geography and Planning and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, China; 2. School of Geographic Sciences Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China]
Abstract:The dynamics of terrestrial carbon are a key factor driving climate change and are greatly influenced by terrestrial processes. Land-use changes as a specific terrestrial process extensively influence terrestrial carbon storage through the alteration of biomass and soil organic matters. However, the direct effect of future land-use changes on terrestrial carbon storage is limited by the refinement of future land-use simulation. In this paper, we propose a FLUS-InVEST (future land use simulation-Integrate valuation of ecosystem services and trade-offs) model to assess the impact of projected land-use change on terrestrial carbon storage in China. The FLUS-InVEST model is composed of fine land-use projection and terrestrial carbon change detecting. Based on the representative showed that: 1) the area with deceased carbon storage shifts from North China to Northeast and the area with increased concentration pathways (RCPs) scenarios, we projected a future land-use change with 30 m resolution for 2100 in China and simulated the changing in terrestrial carbon storage. The FLUS results had a Kappa value of 0.74 and an overall accuracy with 0.80, which indicated that the FLUS performed well in fine land-use projection on a national scale. In addition, carbon storage shifted from Northwest to Southwest between 1995 and 2010. 2) In the RCPs scenario, carbon storage in the forests continues to increase, but decreased in grassland. Specifically, the carbon storage in ?he forest was predicted to increase by 2 332.64 Tg (1 Tg = 1012 g) and 1 754.59 Tg in RCP 6.0 and RCP 8.5, respectively. The carbon storage in grassland was predicted to decrease by 1 719.03 Tg and 2 468.80 Tg in RCP 6.0 and RCP 8.5, respectively. 3) In RCP 6.0, the carbon stored in aboveground vegetation and soil was projected to increase by 127.12 and 83.67 Tg. Conversely, the carbon stored in RCP 8.5 was projected to decrease by 24.67 Tg and 32.41 Tg in aboveground vegetation and soil, respectively, which indicated that RCP 6.0 contributes more to the future carbon sink than RCP 8.5. 4) In the RCPs scenario, the area with increased carbon was mainly located in lines of Hengduan-Qinling-Taihang-Great Khingan and Xufeng-Taihang-Great Khingant, and the area with decreased carbon was distributed throughout the Yunnan-Guizhou Plateau, Sichuan Basin, and Beijing-Tianjing-Hebei Region.
Keywords:land-use change  FLUS-InVEST model  representative concentration pathways  carbon storage  China  
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