基于FLUS与InVEST模型的北京市生态系统碳储量时空演变与预测
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国家自然科学青年科学基金项目(72004014);教育部人文社会科学研究青年基金(18YJC760146);北京林业大学建设世界一流学科和特色发展引导专项基金(2019XKJS0317)


Spatio-temporal evolution and prediction of carbon storage in Beijing's ecosystem based on FLUS and InVEST models
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    摘要:

    城市地区虽然只占世界陆地面积的2%,却产生了全球约75%的碳排放,而科学合理的土地利用和管理方式可以重新固定大约60%-70%已耗损的碳。因此基于土地利用类型核算碳储量并探究城市土地利用变化其对碳储量的影响,能够揭示碳储量时空变化规律,为双碳目标下国土空间规划提供科学依据。基于1990-2018年北京市土地利用数据,利用InVEST模型测算1990-2018年北京市碳储量变化,再利用FLUS模型,分别测算自然演变情景、人口疏解城市发展情景、绿色集约生态保护情景3个城市发展情景下的土地利用变化,接着采用InVEST模型预测2035年3种情景下的碳储量变化,最后借助空间自相关模型对其进行分区管理研究,并基于此提出北京市未来城市发展与低碳城市建设规划建议。基于研究得出以下结果:(1)2000-2010年是碳流失较严重时期,碳储量下降了4.3%,而2010年后碳流失相对缓和,且在2015年后得到明显改善,2010年至2018年碳储量提升了3.5%。(2)除自然演变情景外,两种情景下的未来碳储量预测值均会进一步增加,且绿色集约生态保护情景的碳储量预测值最高,为16.39×106 t,比最低的自然演变情景高出7.5×105 t。(3)局部空间自相关分析结果显示,3种情景下的碳储量值在空间分布上具有相似性,碳储量高值区域在城市北部、西北部及西部区域出现集聚,低值区域则在中心城区聚集。

    Abstract:

    Urban areas, which take only 2% of the world's land territory, have generated approximately 75% of global carbon emissions. Therefore, calculating carbon storage based on land use type and exploring the impact of urban land use change on carbon storage can reveal the spatio-temporal change rules of carbon storage and provide scientific basis for the national spatial planning under the dual carbon target. Based on the land use data, InVEST model was used to estimate the change of carbon storage in Beijing from 1990 to 2018, and FLUS model was used to predict the land use change under three urban development scenarios:natural evolution scenario, population distribution and urban development scenario, and green intensive ecological protection scenario. Then InVEST model was used to predict the change of carbon storage under the three scenarios in 2035. Finally, the spatial autocorrelation model was used to study the zoning management of the three scenarios, and the suggestions for the future urban development and low-carbon urban construction planning of Beijing were proposed. Based on the research, the following results were obtained:(1) from 2000 to 2010, carbon storage decreased by 4.3%. After 2010, carbon loss was relatively moderate, and improved significantly after 2015. From 2010 to 2018, the carbon storage increased by 3.5%. (2) Except for the Natural Evolution Scenario(NES), the predicted value of carbon storage under the two scenarios would further increase, and the predicted value of carbon storage under the GIEPS(Green Intensive Evolution Protection Scenario) was the highest, which was 16.39×106 t, 7.5×106 t more than that of NES. (3) The local spatial autocorrelation analysis showed that the carbon storage values under the three scenarios were similar in spatial distribution, and the high carbon storage values were clustered in Huairou, Yanqing, Changping and Mentougou districts in the north, northwest and west of the city.

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邵壮,陈然,赵晶,夏楚瑜,何颖婷,唐丰芸.基于FLUS与InVEST模型的北京市生态系统碳储量时空演变与预测.生态学报,2022,42(23):9456~9469

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