Temporal and Spatial Evolution of Carbon Storage in Guiyang City Based on PLUS-InVEST Model and Multi-scenario Simulation and Prediction

Li Huyue; Dai Quanhou; Hu Zeyin; Gui Yuxiang

doi:10.13961/j.cnki.stbctb.20240329.001

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Temporal and Spatial Evolution of Carbon Storage in Guiyang City Based on PLUS-InVEST Model and Multi-scenario Simulation and Prediction

- Temporal and Spatial Evolution of Carbon Storage in Guiyang City Based on PLUS-InVEST Model and Multi-scenario Simulation and Prediction
- Bulletin of Soiland Water Conservation Vol. 44, Issue 3, Pages: 441-451(2024)
- 作者机构：
  
  贵州大学林学院,贵州,贵阳,550025
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.20240329.001
  CLC： X171.1
- Published：2024
- 稿件说明：
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Li Huyue, Dai Quanhou, Hu Zeyin, et al. Temporal and Spatial Evolution of Carbon Storage in Guiyang City Based on PLUS-InVEST Model and Multi-scenario Simulation and Prediction[J]. Bulletin of Soiland Water Conservation, 2024, 44(3): 441-451.
DOI：

Li Huyue, Dai Quanhou, Hu Zeyin, et al. Temporal and Spatial Evolution of Carbon Storage in Guiyang City Based on PLUS-InVEST Model and Multi-scenario Simulation and Prediction[J]. Bulletin of Soiland Water Conservation, 2024, 44(3): 441-451. DOI： 10.13961/j.cnki.stbctb.20240329.001.

摘要

[目的

]

分析贵州省贵阳市历史和未来时间序列下碳储量时空演变特征，为促进区域可持续发展提供科学依据。[方法

]

以贵阳市为例，利用ArcGIS评估2000—2020年贵阳市的土地利用变化与碳储量时空演变特征，并耦合PLUS，InVEST模型预测2030年不同发展情景下土地利用空间格局及其碳储量变化。[结果

]

①2000—2020年贵阳市土地利用变化为耕地和草地转化为水域和建设用地；耕地面积减少了190 km

；草地面积减少了188 km

；水域面积增加了43 km

；建设用地面积锐增了367 km

。 ②2000—2020年贵阳市碳储总量呈现先增加后下降趋势，共降低了2.197×10

t，在空间上呈现北高南低的分布格局，北部区域是贵阳市的主要碳汇功能区，建设用地扩张是影响研究区碳储量降低的主要原因。 ③2030自然情景、耕地保护和生态保护情景下建设用地分别扩张了279，193，175 km

，增幅为51.48％，35.61％，32.29％。 ④2030年自然情景、耕地保护和生态保护情景下的碳储总量分别为1.400×10

，1.398×10

，1.410×10

t，相较于2020年均有下降。碳储量在空间上始终表现为北高南低的分布格局，生态保护情景下更有利于减缓研究区碳储量的下降趋势。[结论

]

未来贵阳市在生态环境方面可继续加强实施退耕还林政策来恢复碳储量水平，而在城市发展方面，应该制定更加合理的综合发展战略，在经济发展的同时又能兼顾生态保护。

Abstract

[Objective] The spatial and temporal evolution characteristics of carbon storage in Guiyang City

Guizhou Province

in the historical and future time series were analyzed in order to provide a scientific basis for the promotion of regional sustainable development. [Methods] ArcGIS was used to assess the spatial and temporal evolution characteristics of land use changes and carbon stocks in Guiyang City from 2000 to 2020. The coupled PLUS-InVEST model was used to predict the spatial pattern of land use

and the carbon stock change under different development scenarios in 2030. [Results] ① From 2000 to 2020

land use changes in Guiyang City came from the conversion of arable land and grassland into water areas and construction land. The area of arable land decreased by 190 km2. The area of grassland decreased by 188 km2. The water area increased by 43 km2. The area of construction land increased sharply by 367 km2. ② The total carbon storage of Guiyang City from 2000 to 2020 was characterized by the spatial evolution of carbon storage in different development scenarios. The total carbon storage of Guiyang City during 2000—2020 initially increased and then decreased

with a total decrease of 2.197×106 t. The spatial distribution pattern was characterized as high in the north and low in the south

and the northern region was the main carbon sink functional area of Guiyang City. The expansion of the construction land area was the main factor decreasing carbon storage in the study area. ④ Under the natural

arable land protection

and ecological protection scenarios for 2030

the area of construction land expanded by 279

193

and 175 km2

respectively

with increases of 51.48%

35.61%

and 32.29%. ④ The total carbon storage under the natural

arable land protection

and ecological protection scenarios for 2030 were 1.400×108

1.398×108

and 1.410×108 t

respectively

and these values had decreased from the values in 2020. The carbon storage always showed a spatial distribution pattern of high in the north and low in the south. The ecological protection scenario was more conducive to slowing down the declining trend of carbon storage in the study area. [Conclusion] In the future

Guiyang City should continue to strengthen the policy implementaion of returning farmland to forest land in order to restore the carbon storage level in terms of the ecological environment. In terms of urban development

a more reasonable and comprehensive development strategy should be formulated to take into account ecological protection while developing the economy.

关键词

Keywords

references

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.Chen Meijing, Wang Qingri, Bai Zhongke, et al. Transition of “production-living-ecological” space and its carbon storage effect under the vision of carbon neutralization: A case study of Guizhou Province [J]. China Land Science, 2021,35(11):101-111.

王志远,吴凡,万鼎等.多情景模拟区域土地利用变化对碳储量的影响[J].中国环境科学,2023,43(11):6063-6078.Wang Zhiyuan, Wu Fan, Wan Ding, et al. Many scenario simulation of regional land use change on the influence of carbon [J]. China environmental science, lancet, 2023(11): 6063-6078.

Environmental Monitoring; Researchers from department of the environment discuss findings in environmental monitoring (scenario modeling for spatial-temporal change detection of carbon storage and sequestration in a forested landscape in Northern Iran) [J]. Ecology Environment & Conservation, 2018.

郭义强,郧文聚,黄妮,等.土地整理工程对土壤碳排放的影响[J].土壤通报,2016,47(1):36-41.Guo Yiqiang, Yun Wenju, Huang Ni, et al. The effect of land consolidation projects on soil carbon emissions [J]. Chinese Journal of Soil Science, 2016,47(1):36-41.

毛永发,周启刚,王陶,等.耦合PLUS-InVEST-Geodector模型的三峡库区碳储量时空变化及其定量归因[J].长江流域资源与环境,2023,32(5):1042-1057.Mao Yongfa, Zhou Qigang, Wang Tao, et al. Spatial-temporal variation of carbon storage and its quantitative attribution in the Three Gorges reservoir area coupled with PLUS-InVEST Geodector model [J]. Resources and Environment in the Yangtze Basin, 2023,32(5):1042-1057.

曾伟生.东北落叶松林碳储量生长模型研建及固碳能力分析[J].林业资源管理,2022(1):18-23.Zeng Weisheng. Development of carbon growth models and analysis of carbon sequestration capacity for larch forest stands in the northeast of China [J]. Forest Resources Management, 2022(1):18-23.

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.

赵胤程,覃盟琳,庞雅月,等.基于FLUS-InVEST模型的北部湾城市群生态空间碳汇演变模拟及驱动因素研究[J].水土保持通报,2022,42(3):345-355.Zhao Yincheng, Qin Menglin, Pang Yayue, et al. Evolution simulation and driving factors of eco-spatial carbon sinks in Beibu Gulf urban agglomeration based on FLUS-InVEST model [J]. Bulletin of Soil and Water Conservation, 2022,42(3):345-355.

庄子薛,谢梦晴,张文萍,等.基于FLUS-InVEST模型的碳储量时空变迁及多情景模拟预测:以成德眉资地区为例[J].风景园林,2022,29(5):38-44.Zhuang Zixue, Xie Mengqing, Zhang Wenping, et al. Temporal and spatial changes and multi-scenario simulation prediction of carbon storage based on FLUS-InVEST model: A case study of Chengdu-Deyang-Meishan-Ziyang area [J]. Landscape Architecture, 2022,29(5): 38-44.

伍丹,朱康文,张晟,等.基于PLUS模型和InVEST模型的成渝经济区碳储量演化分析[J].三峡生态环境监测,2022,7(2):85-96.Wu Dan, Zhu Kangwen, Zhang Sheng, et al. Evolution analysis of carbon stock in Chengdu-Chongqing Economic Zone based on PLUS model and InVEST model [J]. Ecology and Environmental Monitoring of Three Gorges, 2022,7(2):85-96.

王超越,郭先华,郭莉,等.基于FLUS-InVEST的西北地区土地利用变化及其对碳储量的影响:以呼包鄂榆城市群为例[J].生态环境学报,2022,31(8):1667-1679.Wang Chaoyue, Guo Xianhua, Guo Li, et al. Land use change and its impact on carbon storage in Northwest China based on FLUS-invest: A case study of Hu-Bao-Er-Yu urban agglomeration [J]. Ecology and Environmental Sciences, 2022,31(8):1667-1679.

杨宇萍,胡文敏,贾冠宇,等.基于InVEST与ANN-CA模型的环洞庭湖区土地利用碳储量情景模拟[J].南京林业大学学报(自然科学版),2023,47(4):175-184.Yang Yuping, Hu Wenmin, Jia Guanyu, et al. Scenario simulation integrating the ANN-CA model with the InVEST model to investigate land-based carbon storage in Dongting Lake area [J] Journal of Nanjing Forestry University (Natural Science Edition), 2023,47(4):175-184.

王成武,罗俊杰,唐鸿湖.基于InVEST模型的太行山沿线地区生态系统碳储量时空分异驱动力分析[J].生态环境学报,2023,32(2):215-225.Wang Chengwu, Luo Junjie, Tang Honghu. Analysis on the driving force of spatial and temporal differentiation of carbon storage in the Taihang Mountains based on InVEST model [J]. Ecology and Environmental Sciences, 2023,32(2):215-225.

卿苗,赵军,冯超,等.1980—2030年石羊河流域生态系统碳储存服务对土地利用变化的响应[J].生态学报,2022,42(23):9525-9536.Qing Miao, Zhao Jun, Feng Chao, et al. Response of ecosystem carbon storage service to land-use change in Shiyang River basin from 1980 to 2030[J]. Acta Ecologica Sinica, 2022,42(23): 9525-9536.

Ismaili Alaoui H, Chemchaoui A, El Asri B, et al. Modeling predictive changes of carbon storage using invest model in the Beht watershed (Morocco) [J]. Modeling Earth Systems and Environment, 2023,9(4):4313-4322.

高述超,陈毅青,陈宗铸,等.海南岛森林生态系统碳储量及其空间分布特征[J].生态学报,2023,43(9):3558-3570.Gao Shuchao, Chen Yiqing, Chen Zongzhu, et al. Carbon storage and its spatial distribution characteristics of forest ecosystems in Hainan Island, China [J]. Acta Ecologica Sinica, 2023,43(9):3558-3570.

韩旭超,高丹丹,李顺龙.运用森林蓄积量换算因子法及灰色预测模型对黑龙江省森林增汇潜力的估测[J].东北林业大学学报,2023,51(10):70-73.Han Xuchao, Gao Dandan, Li Shunlong. Forest carbon sequestration potential in Heilongjang Province using forest stock conversion factor and gray prediction model [J]. Journal of Northeast Forestry University, 2023,51(10):70-73.

帕茹克·吾斯曼江,艾东,方一舒,等.基于InVEST与CA-Markov模型的昆明市碳储量时空演变与预测[J].环境科学, 2024,45(1):287-299.Parjuk Usman Jiang, Ai Dong, Fang Yishu, et al. Temporal and spatial evolution and prediction of carbon storage in Kunming City based on InVEST and CA-Markov model [J]. Environmental Science, 2024,45(1):287-299.

李小军,车良革,胡宝清.FLUS-InVEST模型的北海市生态系统碳储量时空差异分析[J].测绘通报,2023(6):117-123.Li Xiaojun, Che Liangge, Hu Baoqing. Spatio-temporal difference analysis of carbon storage in Beihai’s ecosystem based on FLUS-InVEST models [J]. Bulletin of Surveying and Mapping, 2023(6):117-123.

Shaw C H, Hilger A B, Metsaranta J, et al. Evaluation of simulated estimates of forest ecosystem carbon stocks using ground plot data from Canada’s national forest inventory [J]. Ecological Modelling, 2014,272:323-347.

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.

Tian Lei, Tao Yu, Fu Wenxue, 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.

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.

Basu T, Das A, Das K, et al. Urban expansion induced loss of natural vegetation cover and ecosystem service values: A scenario-based study in the Siliguri municipal corporation (Gateway of North-East India) [J]. Land Use Policy, 2023,132:106838.

Broadbent C D, Brookshire D S, Goodrich D, et al. Developing ecological endpoints for valuation of semi-arid riparian ecosystem services [J]. Journal of Environmental Planning and Management, 2023,66(13):2760-2777.

罗笑,卢鹏.贵州省喀斯特区土地利用变化及驱动力分析[J].贵州林业科技,2022,50(4):22-27.Luo Xiao, Lu Peng. Land use change and driving force in Karst area of Guizhou Province [J]. Guizhou Forestry Science and Technology, 2022,50(4):22-27.

魏媛,吴长勇,徐筑燕.贵阳市土地利用变化对生态系统服务价值的影响[J].贵州农业科学,2015,43(2):185-188.Wei Yuan, Wu Changyong, Xu Zhuyan. Effects of land use variations on ecosystem services value of Guiyang City [J]. Guizhou Agricultural Sciences, 2015,43(2):185-188.

张美琪,陈波,赵敏.贵州省湿地碳储量与碳中和潜力分析[J].地质科技通报,2023,42(2):315-326.Zhang Meiqi, Chen Bo, Zhao Min. Analysis of the carbon stock and carbon neutral potential of wetlands in Guizhou Province [J]. Bulletin of Geological Science and Technology, 2023,42(2):315-326.

谭远模,谢思梅,谢荣安.土地利用时空变化与城市化发展分析[J].测绘通报,2020(4):139-142.Tan Yuanmo, Xie Simei, Xie Rongan. Analysis of spatial and temporal change of land use and urbanization development [J]. Bulletin of Surveying and Mapping, 2020(4):139-142.

吴楠,陈凝,程鹏,等.安徽省陆地生态系统碳储量变化对未来土地覆被情景的响应[J].长江流域资源与环境,2023,32(2):415-426.Wu Nan, Chen Ning, Cheng Peng, et al. Evaluation of carbon storage on terrestrial ecosystem responses to land cover change under five future scenarios in Anhui Province [J]. Resources and Environment in the Yangtze Basin, 2023,32(2): 415-426.

付帅,彭雨欣,徐炳先.基于PLUS与InVEST模型的鄱阳湖流域碳储量时空变化与预测[J].环境工程,2023,41(10):163-172.Fu Shuai, Peng Yuxin, XU Bingxia, Spatial-temporal change and prediction of carbon storage in Poyang Lake basin based on PLUS and InVEST model [J]. Environmental Engineering, 2019,41(10):163-172.

周伟婷.基于土地利用变化的贵阳市碳排放时空演变和空间关联[J].湖北农业科学,2023,62(5):8-13.Zhou Weiting. Spatio-temporal evolution and spatial correlation of carbon emissions in Guiyang City based on land use change [J]. Hubei Agricultural Sciences, 2023,62(5):8-13.

唐璐,李娟,王丹丹,等.2010—2020年贵阳市高质量发展与水资源保护利用的耦合协调关系[J].水土保持通报,2023,43(1):235-243.Tang Lu, Li Juan, Wang Dandan, et al. Coupling coordination of high-quality development with water resource protection and utilization in Guiyang City during 2010—2020[J]. Bulletin of Soil and Water Conservation,2023,43(1): 235-243.

景晓玮. 基于InVEST模型的贵州省生态系统服务计量及价值评估研究[D]. 江苏南京：南京林业大学，2021.Jing Xiaowei. Research on the measurement and value evaluation of ecosystem services in Guizhou Province based on InVEST model [D]. Nanjing, Jiangsu: Nanjing Forestry University, 2021.

陈田田,黄强,王强.基于地理探测器的喀斯特山区生态系统服务关系分异特征及驱动力解析:以贵州省为例[J].生态学报,2022,42(17):6959-6972.Chen Tiantian, Huang Qiang, Wang Qiang. Differentiation characteristics and driving factors of ecosystem services relationships in karst mountainous area based on geographic detector modeling: A case study of Guizhou Province [J]. Acta Ecologica Sinica, 2022,42(17):6959-6972.

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.

杨静怡,吴峰.贵阳市1980—2018年土地覆盖类型及碳储量变化研究[J].西南林业大学学报(自然科学),2020,40(4):115-121.Yang Jingyi, Wu Feng. Study on change of land cover type and carbon storage during 1980—2018 in Guiyang [J]. Journal of Southwest Forestry University (Natural Sciences), 2020,40(4):115-121.

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