基于PLUS-InVEST模型碳储量时空演变及驱动因素分析——以纳帕海流域为例

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Abstract Taking the Napa Sea basin as the study area, by using the PLUS-InVEST model and geographic detector methods. Providing a scientific understanding on change pattern of carbon sink function in this basin, evolution patterns of spatial and temporal driving factors of carbon storage were studied over the past 20 years, and the evolution tendency were predicted in future under four kinds of different scenarios based on the PLUS-InVEST model in Napa Sea Basin. The results showed: (1) From 2000 to 2020, water area and construction land respectively increased by 143.98% and 451.86%, and farmland and grassland respectively decreased by 61.37% and 20.53%. Farmland and grassland was mainly transferred to construction land, some grassland transferred to forest land. (2) In the past 20years, carbon storage showed a downward trend, with a total decreased of 0.63×10⁶ tons. Decline of grassland and farmland and increase of construction land were the main reasons for decrease of carbon storage in the basin. (3) Compared carbon storage under different scenarios in 2020with in 2035, its will increase under two kinds of scenarios except for the natural development and cultivated land protection scenario, and total carbon storage will be respectively 18.11×10⁶t, 18.17×10⁶t, 18.31×10⁶ and 18.29×10⁶t for each scenario. (4) DEM (0.533), mean annual temperature (0.442), and NDVI (0.365) were the dominant factors driving the evolution of carbon storage in the basin. (5) The interaction effects among the driving factors was stronger than that of single factors, and synergistic effect of DEM and NDVI (0.633) was the strongest. The results can provide data support for how to improve rationality of land use and function of carbon sink scientifically in Napa Sea Basin.

Key words： carbon storage driving factor Plus-InVEST model geodetector Napa Sea Basin

Received: 11 February 2024

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X171.1

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	ZHANG Shuang
	GAO Qi-chen
	ZHANG Rong
	SONG Chen-hui
	LI Zhong-fei

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ZHANG Shuang,GAO Qi-chen,ZHANG Rong等. Evaluating the changes and driving factors of carbon storage using the PLUS-InVEST Model: A case study of Napa Sea Basin[J]. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(9): 5192-5201.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2024/V44/I9/5192

[1] Houghton R A. Interactions between land-use change and climate-carbon cycle feedbacks [J]. Current Climate Change Reports, 2018, 4:115-127.
[2] Hmn X, Zhao F, Tong X, et al. Understanding soil carbon sequestration following the afforestation of former arable land by physical fractionation [J]. Catena, 2017,150:317-327.
[3] Lai L, Huang X, Yang H, et al. Carbon emissions from land-use change and management in china between 1990 and 2010[J]. Science Advances, 2016,2(11):e1601063.
[4] 廖亮林,周蕾,王绍强,等.2005~2013年中国新增造林植被生物量碳库固碳潜力分析[J]. 地理学报, 2016,71(11):1939-1947. Liao L L, Zhou L, Wang S Q, et al. Carbon sequestration potential of biomass carbon pool for new afforestation in China during 2005~2013[J]. Acta Geographica Sinica, 2016,71(11):1939-1947.
[5] He C Y, Zhang D, Huang Q X, et al. Assessing the potential impacts of urban expansion on regional carbon storage by linking the lusd-urban and invest models [J]. Environmental Modelling & Software, 2016,75: 44-58.
[6] 方精云,于贵瑞,任小波,等.中国陆地生态系统固碳效应——中国科学院战略性先导科技专项“应对气候变化的碳收支认证及相关问题”之生态系统固碳任务群研究进展[J]. 中国科学院院刊, 2015,30(6):848-857,875. Fang J Y, Yu G R, Ren X B,et al. Carbon Sequestration in China’s Terrestrial Ecosystems under Climate Change——Progress on Ecosystem Carbon Sequestration from the CAS Strategic Priority Research Program [J]. Bulletin of Chinese Academy of Sciences, 2015,30(6):848-857,875.
[7] Vizcaíno-Bravo Q, Williams-Linera G,Asbjornsen H. Biodiversity and carbon storage are correlated along a land use intensity gradient in a tropical montane forest watershed, mexico [J]. Basic and Applied Ecology, 2020,44:24-34.
[8] 李世锋,洪增林,薛旭平,等.基于logistic-ca-markov耦合模型的彬州市lucc多情景模拟[J]. 水土保持研究, 2022,29(4):292-299. Li S F, Hong Z L, Xue X P, et al. Multi-Scenario Simulation of LUCC in Binzhou City Based on Logistic-CA-Markov Coupling Model [J]. Research of Soil and Water Conservation, 2022,29(4):292-299.
[9] 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):1-11. Fang J Y, Zhong C R, Wang F X, et al. Spatial-temporal Evolution and Prediction of Ecosystem Carbon Storage on Hainan Island by Coupling InVEST and FLUS Model [J]. Bulletin of Soil and Water Conservation, 2023,43(5):1-11.
[10] 许小亮,李鑫,肖长江,等.基于clue-s模型的不同情景下区域土地利用布局优化[J]. 生态学报, 2016,36(17):5401-5410.Xu X L, Li X, Xiao C J, et al. Land Use layout optimization under different scenarios by using the CLUE-S model [J]. Acta Ecologica Sinica, 2016,36(17):5401-5410.
[11] 喇蕗梦,勾蒙蒙,李乐,等.三峡库区生态系统服务权衡时空动态与情景模拟:以秭归县为例[J]. 生态与农村环境学报, 2021,37(11): 1368-1377. La L M, Gou M M, Li L, et al. Spatiotemporal Dynamics and Scenarios Analysis on Trade-offs between Ecosystem Service in Three Gorges Reservoir Area: A Case Study of Zigui County [J]. Journal of Ecology and Rural Environment, 2021,37(11):1368-1377.
[12] 杜怀玉,俞金凤,张媛,等.石羊河流域多情景土地利用优化及碳储量评估[J]. 环境科学, 2024,45(7):4164-4176. Du H Y, Yu J F, Zhang Y, et al. Land Use Optimization and Carbon Reserve Assessment in the Shiyang River Basin [J]. Environmental Science, 2024,45(7):4164-4176.
[13] 赫晓慧,徐雅婷,范学峰,等.中原城市群区域碳储量的时空变化和预测研究[J]. 中国环境科学, 2022,42(6):2965-2976 He X H, Xu Y T, Fan X F, et al. Temporal and spatial variation and prediction of regional carbon storage in Zhongyuan Urban Agglomeration [J]. China Environmental Science, 2022,42(6):2965-2976
[14] 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 T, Yang M Z, Wu D F, 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.
[15] 王想,王春雨,吕飞南,等.基于plus-invest模型的区县碳储量时空格局变化与碳汇提升策略——以延庆区为例[J]. 应用生态学报, 2023,34(12):3373-3384. Wang X, Wang C Y, Lu F N, et al. Temporal and spatial variations of carbon storage and carbon sink improvement strategy at the district and county level based on PLUS?InVEST model: Taking Yanqing District as an example [J]. Chinese Journal of Applied Ecology, 2023,34(12):3373-3384.
[16] Dangulla M, Abd Manaf L, Ramli M F, et al. Exploring urban tree diversity and carbon stocks in zaria metropolis, north western nigeria [J]. Applied Geography, 2021,127:102385.
[17] Bhutia P L, Gupta B, Yadav R P, et al. Soil carbon stock and floristic biomass carbon under different agroforestry systems along an elevation gradient [J]. Agrochimica, 2022,66(1):61-76.
[18] 吴恒,胥辉.森林植被碳密度遥感反演和校准研究[J]. 林业资源管理, 2021,(6):43-51. Wu H, XUu H. Ｒemote Sensing Ｒetrieval and Calibration of Forest Vegetation Carbon Density Based on Time-series Data [J]. Forest and Grassland Resources Research, 2021,(6):43-51.
[19] 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 M Q, Chen B, Zhao M. Analysis of the carbon stock and carbon neutral potential of wetlands in Guizhou Province [J]. Bulletin of Geological Scienceand Technology, 2023,42(2):315-326.
[20] Mauya E W, Mugasha W A, Njana M A, et al. Carbon stocks for different land cover types in mainland tanzania [J]. Carbon Balance and Management, 2019,14(4):1-12.
[21] 张凯琪,陈建军,侯建坤,等.耦合InVEST与GeoSOS-FLUS模型的桂林市碳储量可持续发展研究[J]. 中国环境科学, 2022,42(6):2799-2809. Zhang K Q, Chen J J, Hou J K, et al. Study on sustainable development of carbon storage in Guilin coupled with InVEST and GeoSOS-FLUS model [J]. China Environmental Science, 2022,42(6): 2799-2809.
[22] 刘冠,李国庆,李洁,等.基于invest模型的1999~2016年麻塔流域碳储量变化及空间格局研究[J]. 干旱区研究, 2021,38(1):267-274. Liu G, Li G Q, Li J, et al. Study on change in carbon storage and its spatial pattern in Mata Watershed from 1999to 2016based on InVEST model [J]. Arid Zone Research, 2021,38(1):267-274.
[23] Lu F, Hu H F, Sun W J, et al. Effects of national ecological restoration projects on carbon sequestration in china from 2001 to 2010[J]. Proceedings of the National Academy of Sciences of the United States of America, 2018,115(16):4039-4044.
[24] Lipatov D N, Shcheglov A I, Manakhov D V, et al. Spatial variation of organic carbon stocks in peat soils and gleyzems in the northeast of sakh^alin island [J]. Eurasian Soil Science, 2021,54(2):226-237.
[25] Alaoui H I, Chemchaoui A, El A 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.
[26] Piyathilake I, Udayakumara E P N, Ranaweera L V, et al. Modeling predictive assessment of carbon storage using invest model in uva province, sri lanka [J]. Modeling Earth Systems and Environment, 2022,8(2):2213-2223.
[27] Kohestani N, Rastgar S, Heydari G, et al. Spatiotemporal modeling of the value of carbon sequestration under ch^anging land use/land cover using invest model: A case study of nour-rud watershed, northern iran [J]. Environment Development and Sustainability, 2023:1-29.
[28] Hashim T, Suratman M N, Singh H R, et al. Predictive Model of Mangroves Carbon Stocks in Kedah, Malaysia using Remote Sensing [C]//IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2020,540(1):012033.
[29] Henson I E. A review of models for assessing carbon stocks and carbon sequestration in oil palm plantations [J]. Journal of Oil Palm Research, 2017,29(1):1-10.
[30] 邱建慧.围填海活动对中国滨海湿地碳储量的影响研究[D]. 厦门:厦门大学, 2017. Qiu J H. Coastal reclamation impacts on carbon storage in China scoastal wetland [D]. Xiamen: Xiamen University, 2017.
[31] 邱铃珂,曾文,戴玥,等.巨灾胁迫下植被碳储量地域分异规律研究[J]. 灾害学, 2022,37(4):115-122. Qiu L K, Zang W, Dai Y, et al. Study on the Spatial Heterogeneity of Vegetation Carbon Storage Regarding to Catastrophic Stress [J]. Journal of Catastrophology, 2022,37(4):115-122
[32] Nel L, Boeni A F, Prohaszka V J, et al. Invest soil carbon stock modelling of agricultural landscapes as an ecosystem service indicator [J]. Sustainability, 2022,14(16):9808.
[33] 王犇,甄志磊,席茹阳,等.不同情景下太原市土地利用及碳储量变化研究[J]. 环境科学与技术, 2023,46(10):219-227. Wang B, Zhen Z L, Xi R Y, et al. Land use and carbon stock changes in Taiyuan under different scenarios [J]. Environmental Science & Technology, 2023,46(10):219-227.
[34] 陈绮桐,林锦耀.多情景下珠江三角洲地区土地利用变化对生态系统服务的影响预测[J]. 生态与农村环境学报, 2024,40(5):612-621. Chen Q T, Lin J Y. Prediction of the Impact of Land Use Change on Ecosystem Service in the Pearl River Delta under Different Scenarios [J]. Journal of Ecology and Rural Environment, 2024,40(5):612-621.
[35] Nyamari N,Cabral P. Impact of land cover changes on carbon stock trends in kenya for spatial implementation of redd plus policy [J]. Applied Geography, 2021,133:102479.
[36] 巩晟萱,张玉虎,李宇航.基于plus-invest模型的京津冀碳储量变化及预测[J]. 干旱区资源与环境, 2023,37(6):20-28. Gong S X, Zhang Y H, Li Y H. Spatio－temporal variation and prediction of carbon storage in Beijing－Tianjin－Hebei region－A PLUS－InVEST model approach [J]. Journal of Arid Land Resources and Environment, 2023,37(6):20-28.
[37] 刘涛,刘晓龙,郭利彪,等.基于markov-plus和invest模型的锡林郭勒草原碳储量变化预测[J]. 草原与草坪, 2023,43(2):1-12. Liu T, Liu X L, Guo L B, et al. Prediction of carbon storage change in Xilingol grassland based on Markov-PLUS and inVEST models [J]. Grassland and Turf, 2023, 43(2):1-12.
[38] 肖德荣,田昆,袁华,等.滇西北高原典型退化湿地纳帕海植物群落景观多样性[J]. 生态学杂志, 2007,(8):1171-1176. Xiao D R, Tian K, Yuan H, et al. Land scape diver sity of Napahai wetland plant community in Northwest Yunnan of China [J]. Chinese Journal of Ecology, 2007,(8):1171-1176.
[39] 刘攀,陆梅,李聪,等.纳帕海典型草甸群落土壤有机碳储量及碳组分变化特征[J]. 浙江农林大学学报, 2023,40(2):274-284. Liu P, Lu M, Li C, et al. Changes of soil organic carbon storage and carbon components in typical meadow communities in Napahai [J]. Journal of Zhejiang A & F University, 2023,40(2):274-284.
[40] 田昆,陆梅,常凤来,等.云南纳帕海岩溶湿地生态环境变化及驱动机制[J]. 湖泊科学, 2004,(1):35-42. Tian K, Lu M, Chang L F, et al. The Ecological Environment Degradation and Degradation Mechanism Of Napahai Karst WetIand in Southwestern Yunnan Plateau [J]. Journal of Lake Sciences, 2004, (1):35-42.
[41] 吕晶花,李聪,杨志东,等.纳帕海高原湿地土壤微生物群落对土地利用方式改变的响应[J]. 土壤通报, 2023,54(3):682-694. Lu J H, Li C, Yang Z D, et al. Responses of Soil Microbial Communities to Land Use Changes in the Napahai Plateau Wetlands [J]. Chinese Journal of Soil Science, 2023,54(3):682-694.
[42] 李宁云,田昆,杨宇明,等.滇西北纳帕海湿地景观变化及其评价研究[J]. 西部林业科学, 2012,41(2):27-32. Li N Y, Tian K, Yang Y M, et al. Landscape Change and Assessment of Napahai Wetland in Northwestern Yunnan [J]. Journal of West China Forestry Science, 2012,41(2):27-32.
[43] 栗忠飞,王小莲,徐钰涛,等.1996~2015年滇西北香格里拉植被净初级生产力变化[J]. 生态学报, 2022,42(1):266-276. Li Z F, Wang X L, Xu Y T,et al. Changes of Net Primary Productivity of vegetation from 1996 to 2015 in Shangri La region, China [J]. Acta Ecologica Sinica, 2022,42(1):266-276.
[44] 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 J, Yang D H, Wu Z F, et al. Dynamic simulation of landuse changes and assessment of carbon storage in Kunming City based on PLUS and InVEST models [J]. Bulletin of Soiland Water Conservation, 2023,43(1):378-387.
[45] 边蕊,赵安周,刘宪锋,等.关中平原城市群土地利用变化对碳储量的影响[J]. 环境科学, 2024,45(6):3260-3269. Bian R, Zhao A Z, Liu X F, et al. Impact of Land Use Change on Carbon Storage in Urban Agglomerations in the Guanzhong Plain [J]. Environmental Science, 2024,45(6):3260-3269.
[46] 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 S Q, Hu X M, Sun Y, 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.
[47] 薛健,李宗省,陈雪娇,等.2000~2020年河西地区生态系统服务功能时空变化与影响因素分析[J]. 环境生态学, 2023,5(7):1-12. Xue J, Li Z S, Chen X J, et al. Spatial and temporal variation of ecosystem service functions in the Hexi region from 2000 to 2020 and its influence factors analysis [J]. Environmental Ecology, 2023,5(7): 1-12.
[48] 莫金宵.碳中和背景下基于固碳效应评价及预测的滇中城市群土地利用对策研究[D]. 昆明:云南财经大学, 2023. Mo J X. Research on land use countermeasures of urban agglomeration in central Yunnan based on carbon sequestration effect evaluation and prediction under the background of carbon neutrality [D]. Kunming: Yunnan University of Finance and Economics, 2023.
[49] 杨元合,石岳,孙文娟,等.中国及全球陆地生态系统碳源汇特征及其对碳中和的贡献[J]. 中国科学:生命科学, 2022,52(4):534-574. Yang Y H, Shi Y, Sun W J, et al. Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality. Sci China Life Sci, 2022,52(4):534-574.
[50] 岳彩荣.香格里拉县森林生物量遥感估测研究[D]. 北京:北京林业大学, 2012. Yue X R. Forest Biomass Estimation in Shangri-La County Based on Remote Sensing [D]. Beijing: Beijing Forestry University, 2012.
[51] 孙兴齐.基于invest模型的香格里拉市生态系统服务功能评估[D]. 昆明:云南师范大学, 2017. Sun X Q. Evaluation of ecosystem services in Shangri-La based on InVEST model [D]. Kunming: Yunnan Normal University, 2017.
[52] 朱超,赵淑清,周德成.1997~2006年中国城市建成区有机碳储量的估算[J]. Chinese Journal of Applied Ecology, 2012,23(5):1195-1202. Zhu C, Zhao S Q, Zhou D C. Organic carbon storage in urban built-up areas of China in 1997~2006[J]. 应用生态学报, 2012,23(5):1195-1202.
[53] 曹桃云.基于随机森林的变量重要性研究[J]. 统计与决策, 2022,38(4):60-63. Cao T Y. Study on the Importance of Variables Based on Random Forest [J]. Statistics & Decision, 2022,38(4):60-63.
[54] 王劲峰,徐成东.地理探测器:原理与展望[J]. 地理学报, 2017,72(1): 116-134. Wang J F, Xu C D. Geodetector: Principle and prospective [J]. Acta Geographica Sinica, 2017,72(1):116-134.
[55] 方林,蔡俊,刘艳晓,等.长三角地区生态系统服务价值动态演化及驱动力分析[J]. 生态与农村环境学报, 2022,38(5):556-565. Fang L, Cai J,Liu Y X, et al. Dynamic evolution of ecosystem service value in Yangtze River Delta and analysis on the driving factors [J]. Journal of Ecology and Rural Environment, 2022,38(5):556-565.
[56] Thompson T M. Modeling the climate and carbon systems to estimate the social cost of carbon [J]. Wiley Interdisciplinary Reviews-Climate Change, 2018, 9(5):e532.
[57] 程鹏飞,王金亮,王雪梅,等.基于样地调查的香格里拉县森林生态系统碳储量与碳密度初步研究[J]. 林业调查规划, 2011,36(4):12-15. Cheng P F, Wang J L, Wang X M, et al. Carbon Storage and Density of Four Main Trees in Shangri-la Based on Plot Data [J]. Forest Inventory and Planning, 2011,36(4):12-15.
[58] 王金亮,程鹏飞,徐申,等.基于遥感信息模型的香格里拉森林生物量估算[J]. 浙江农林大学学报, 2013,30(3):325-329. Wang J L, Cheng P F, Xu S, et al. Forest biomass estimation in Shangri-La based on the remote sensing [J]. Journal of Zhejiang A & F University, 2013,30(3):325-329.
[59] 许泉.南方水田土壤有机碳变化特征及保护性耕作增碳效应研究[D]. 南京:南京农业大学, 2007. Xu Q. Dynamic Characteristics Of S0iI Organic Carbon and Carbon Sequestration Effect Of ConservationaI Farming syste ms in Paddy SoiI of SouthChina [D]. Nanjing:Nanjing Agricultural University, 2007.
[60] 韩玉,丁素婷,杨太保.山西南部中条山生态系统碳储量时空分布及驱动因素[J]. 中国环境科学, 2023,43(3):1298-1306. Han Y, Ding S T, Yang T B. Spatial and temporal distribution and driving factors of carbon storage in Zhongtiao Mountain ecosystem in southern Shanxi Province [J]. China Environmental Science, 2023,43(3):1298-1306.
[61] 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 C W, Luo J J, Tang H H. 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.
[62] 孙健,於静,莫晨剑,等.2000~2020年台州市陆地生态系统碳储量对土地利用变化的响应研究[J]. 中国资源综合利用, 2023,41(3): 185-187. Sun J, Yu J, Mo C J, et al. Study on Response of Carbon Storage of Terrestrial Ecosystem to Land Use Change in Taizhou City from 2000 to 2020[J]. China Resources Comprehensive Utilization, 2023,41(3): 185-187.
[63] Adams A B, Pontius J, Galford G L, et al. Modeling carbon storage across a heterogeneous mixed temperate forest: The influence of forest type specificity on regional-scale carbon storage estimates [J]. Landscape Ecology, 2018,33(4):641-658