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生态系统碳储量的多情景模拟与时空变化——以渝东南为例

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编号 lyqk011786

中文标题 生态系统碳储量的多情景模拟与时空变化——以渝东南为例

作者 刘新  黄豪璐 

作者单位 1. 重庆境壹德景观设计工程有限公司 重庆 400000;
2. 招商局重庆交通科研设计院有限公司 重庆 400067

期刊名称 中国城市林业 

年份 2024 

卷号 22

期号 6

栏目名称 研究论文 

中文摘要 气候变化对人类构成了巨大的威胁,掌握生态系统碳储量的时空变化有助于制定更合理的政策和策略来应对这一问题。文章以渝东南区域为例,应用PLUS及InVEST模型对土地利用及生态系统碳储量进行多情景模拟及评估,并在此基础之上通过最邻近指数、核密度及标准差椭圆对减少区域的空间特征进行分析。结果表明:1)2002—2022年,土地利用类型的转换主要是灌木转换为林地和耕地。在2032年的不同模拟情景下,耕地和建设用地均具有增长的趋势,主要增长来自于林地,其余用地变化的幅度较小。2)2002—2022年碳储量总量在逐渐减少,预计在2032年碳储量仍然是减少的趋势,且碳储量减少的幅度依次为EPS

关键词 生态系统碳储量  土地利用  多情景  时空变化 

基金项目 校企联合研究课题双碳目标下推进河南省体育产业高质量发展的路径研究(SKL-2023-2342)

英文标题 Multi-scenario Simulation and Spatiotemporal Variation of Ecosystem Carbon Storage: A Case Study of Southeast Chongqing

作者英文名 Liu Xin, Huang Haolu

单位英文名 1. Chongqing Realm One Landscape Design Studio, Chongqing 400000, China;
2. Chongqing Communications Research & Design Institute Co., Ltd., China Merchants Chongqing 400067, China

英文摘要 Climate change poses a great threat to human beings, and understanding the spatiotemporal variations of ecosystem carbon storage can help formulate more reasonable policies and strategies to address this issue. This paper takes southeast Chongqing as an example to apply PLUS and InVEST models to simulate and evaluate its land use and ecosystem carbon storage in multiple scenarios, and then analyze the regional spatial characteristics of the storage decreased through the nearest neighbor index, kernel density and standard deviation ellipse. The results show: 1) Between 2002 and 2022, the conversion of land use is concentrated in the conversion of shrubs to forests and croplands. Under different simulated scenarios in 2032, both cropland and construction land present an increasing trend, converted mainly from forestland, while the land uses remain smaller changes; 2) The total carbon storage amount is gradually decreasing from 2002 to 2022. It is expected that the carbon storage will be still in a decreasing trend towards 2032, and the magnitude of carbon storage reduction is ordered as EPS

英文关键词 ecosystem carbon storage;land use;multi-scenario;spatiotemporal variation

起始页码 123

截止页码 132

投稿时间 2024/11/1

作者简介 刘新(1987-),男,硕士,高级工程师,研究方向为景观规划与设计。E-mail:xinliu.jason@gmail.com

通讯作者介绍 黄豪璐(1990-),女,硕士,工程师,研究方向为景观规划与设计。E-mail:278140841@qq.com

E-mail 278140841@qq.com

DOI 10.12169/zgcsly.2024.11.01.0003

参考文献 [1] 唐娇华,李智琦,潘勇军.广州市土地利用变化与碳储量模拟:基于PLUS-InVEST模型分析[J]. 中国城市林业,2024,22(4):61-68.
[2] 江佩宜,戴菲.城市绿地碳汇测算方法研究进展[J]. 中国城市林业,2024,22(1):87-93.
[3] HOUGHTON R A,SKOLE D L,LEFKOWITZ D S.Changes in the landscape of Latin America between 1850 and 1985 II.Net release of CO2 to the atmosphere[J]. Forest Ecology and Management,1991,38(3/4):173-199.
[4] MISHRA U,TORN M S,MASANET E,et al.Improving regional soil carbon inventories:combining the IPCC carbon inventory method with regression Kriging[J]. Geoderma,2012,189:288-295.
[5] SPEROW M.An enhanced method for using the IPCC approach to estimate soil organic carbon storage potential on U.S. agricultural soils[J]. Agriculture,Ecosystems & Environment,2014,193:96-107.
[6] ZHUANG Q W,SHAO Z F,GONG J Y,et al.Modeling carbon storage in urban vegetation:progress,challenges,and opportunities[J]. International Journal of Applied Earth Observation and Geoinformation,2022,114:103058.
[7] 向书江,张骞,王丹,等.近20年重庆市主城区碳储量对土地利用/覆被变化的响应及脆弱性分析[J]. 自然资源学报,2022,37(5):1198-1213.
[8] CAI W B,PENG W T.Exploring spatiotemporal variation of carbon storage driven by land use policy in the Yangtze River Delta Region[J]. Land,2021,10(11):1120.
[9] WANG N F,CHEN X P,ZHANG Z L,et al.Spatiotemporal dynamics and driving factors of county-level carbon storage in the Loess Plateau:a case study in Qingcheng County,China[J]. Ecological Indicators,2022,144:109460.
[10] ZHU G F,QIU D D,ZHANG Z X,et al.Land-use changes lead to a decrease in carbon storage in arid region,China[J]. Ecological Indicators,2021,127:107770.
[11] HU J X,YAN D Y,WANG W L.Estimating carbon stock change caused by multi-scenario land-use structure in urban agglomeration[J]. Sustainability,2023,15(6):5503.
[12] TIAN L,TAO Y,FU W X,et al.Dynamic simulation of land use/cover change and assessment of forest ecosystem carbon storage under climate change scenarios in Guangdong Province,China[J]. Remote Sensing,2022,14(10):2330.
[13] HE Y L,MA J M,ZHANG C S,et al.Spatio-temporal evolution and prediction of carbon storage in Guilin based on FLUS and InVEST models[J]. Remote Sensing,2023,15(5):1445.
[14] WANG Z,ZENG J,CHEN W X.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.
[15] ZHANG C Y,ZHAO L,ZHANG H T,et al.Spatial-temporal characteristics of carbon emissions from land use change in Yellow River Delta region,China[J]. Ecological Indicators,2022,136:108623.
[16] YE X,KUANG H H.Evaluation of ecological quality in southeast Chongqing based on modified remote sensing ecological index[J]. Scientific Reports,2022,12(1):15694.
[17] LIANG X,GUAN Q F,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.
[18] 程明月,姬广兴,黄珺嫦,等.基于PLUS-InVEST模型的陕西省多情景土地覆盖模拟与碳储量评估[J/OL]. 环境科学,2024:1-17[2024-12-30]. https://doi.org/10.13227/j.hjkx.202409068.
[19] GAN L,HALIK V,SHI L,et al.Multi-scenario dynamic prediction of ecological risk assessment in an arid area of Northwest China[J]. Ecological Indicators,2023,154:110727.
[20] LIU Y C,JING Y D,HAN S M.Multi-scenario simulation of land use/land cover change and water yield evaluation coupled with the GMOP-PLUS-InVEST model:a case study of the nansi lake basin in China[J]. Ecological Indicators,2023,155:110926.
[21] SHARP R,Chaplin-Kramer R,WOOD S A,et al.InVEST user's guide[M]. The Natural Capital Project,Stanford University,University of Minnesota,The Nature Conservancy,and World Wildlife Fund,2018.
[22] 万其林,邵景安.2000—2020年三峡库区重庆段土地利用及碳储量估算[J]. 重庆师范大学学报(自然科学版),2023,40(6):52-64.
[23] MAURO F,HAXTEMA Z,TEMESGEN H.Comparison of sampling methods for estimation of nearest-neighbor index values[J]. Canadian Journal of Forest Research,2017,47(6):703-715.
[24] 许泽宁,高晓路.基于电子地图兴趣点的城市建成区边界识别方法[J]. 地理学报,2016,71(6):928-939.
[25] WANG F H,CHEN C,XIU C L,et al.Location analysis of retail stores in Changchun,China:a street centrality perspective[J]. Cities,2014,41:54-63.
[26] 智菲,周振宏,赵铭,等.基于PLUS和InVEST模型的合肥市生态系统碳储量时空演变特征[J]. 水土保持学报,2024,38(2):205-215.
[27] 王子昊,王冰,张宇飞,等.基于PLUS-InVEST模型的呼和浩特市多情景土地利用变化动态模拟及碳储量评估[J]. 农业资源与环境学报,2024,41(2):292-304.
[28] 孙欣欣,薛建辉,董丽娜.基于PLUS模型和InVEST模型的南京市生态系统碳储量时空变化与预测[J]. 生态与农村环境学报,2023,39(1):41-51.
[29] 张鹏,李良涛,苏玉姣,等.基于PLUS和InVEST模型的邯郸市碳储量空间分布特征研究[J]. 水土保持通报,2023,43(3):338-348.
[30] 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.

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