Spatial-temporal change and prediction of carbon stock in the ecosystem of Xi’an based on PLUS and InVEST models
YANG Lianwei1(), ZHAO Juan1, ZHU Jiatian1, LIU Lei1, ZHANG Ping1,2()
1. School of Environmental and Chemical Engineering, Xi’an Polytechnic University, Xi’an 710600, China 2. Shaanxi Key Laboratory of Land Consolidation, Xi’an 710075, China
Land use can cause carbon stock changes by affecting the structural layouts and functions of terrestrial ecosystems. Therefore, research on the relationship between land use changes and carbon stock is greatly significant for optimizing regional land use patterns and making sensible ecological decisions. This study predicted the spatial-temporal changing characteristics of land use and carbon stock in Xi’an under different scenarios in the future using the PLUS and InVEST models and investigated the impact of land use changes on carbon stock. The results are as follows. From 2000 to 2015, the expansion of construction land and the transfer of high-carbon-density land reduced the carbon stock of Xi’an by 2.49×106 t. From 2015 to 2030 the carbon stock continuously declined by 2.14×106 t in the natural growth scenario, and the carbon stock of Xi’an will increase by 6.92×105 t in the ecological protection scenario due to the measures taken for land protection and transfer control. In the cultivated land protection scenario, the cultivated land will be protected, but the high-carbon-density land such as woodland and grassland will be affected by the expansion of construction land during 2015—2030, reducing the carbon stock to 1.60×108 t. As indicated by the analysis of carbon density change, ecological protection measures can increase the changing rate of carbon density. Compared with the natural growth scenario, the ecological protection scenario will increase the proportion of areas with increased carbon density (mainly high-increase areas) from 0.05% to 1.57%. By contrast, under the cultivated land protection scenario, the carbon density will decrease, and high-increase areas will be transformed into moderately-high-increase areas. Based on cultivated land protection, it is necessary to take proper ecological protection measures in the future land use planning of Xi’an to control the rapid expansion of construction land from cultivated and forest land. Optimizing land use patterns can effectively reduce the loss of carbon stock, improve the level of regional carbon stock, and achieve regional sustainable development.
杨潋威, 赵娟, 朱家田, 刘雷, 张平. 基于PLUS和InVEST模型的西安市生态系统碳储量时空变化与预测[J]. 自然资源遥感, 2022, 34(4): 175-182.
YANG Lianwei, ZHAO Juan, ZHU Jiatian, LIU Lei, ZHANG Ping. Spatial-temporal change and prediction of carbon stock in the ecosystem of Xi’an based on PLUS and InVEST models. Remote Sensing for Natural Resources, 2022, 34(4): 175-182.
Zhang Y, Shi X Y, Tang Q. Carbon storage assessment in the upper reaches of the Fenhe River under different land use scenarios[J]. Acta Ecologica Sinica, 2021, 41(1):360-373.
Zhu Z Q, Ma X S, Hu H. Spatio-temporal evolution and prediction of ecosystem carbon stocks in Guangzhou City by coupling FLUS-InVEST models[J]. Bulletin of Soil and Water Conservation, 2021, 41(2):222-229.
Liu Y, Zhang J, Zhou D M, et al. Temporal and spatial variation of carbon storage in the Shule River basin on InVEST model[J]. Acta Ecologica Sinca, 2021, 41(10):4052-4065.
[4]
Jiang W G, Deng Y, Tang Z H, et al. Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models[J]. Ecological Modelling, 2017, 345:30-40.
doi: 10.1016/j.ecolmodel.2016.12.002
Han Y L, Chen K L, Yu D Y. Evaluation on the impact of land use change on habitat quality in Qinghai Lake basin[J]. Ecology and Environmental Sciences, 2019, 28(10):2035-2044.
Wang G, Wang J W. Study on the impact of land use change on habitat quality in Dandong coastal area[J]. Ecology and Environmental Sciences, 2021, 30(3):621-630.
Zhu W B, Zhang J J, Cui Y P, et al. Assessment of territorial ecosystem carbon storage based on land use change scenario:A case study in Qihe River basin[J]. Acta Geographica Sinica, 2019, 74(3):446-459.
[8]
Zhao M, He Z, Du J, et al. Assessing the effects of ecological engineering on carbon storage by linking the CA-Markov and InVEST models[J]. Ecological Indicators, 2019, 98:29-38.
doi: 10.1016/j.ecolind.2018.10.052
Shi M J, Wu H Q, Jia H T, et al. Temporal and spatial evolution and prediction of carbon stocks in Yili Valley based on MCE-CA-Markov and InVEST models[J]. Journal of Agricultural Resources and Environment, 2021, 38(6):1010-1019.
Wu P J, Liu X P, Li X, et al. Impact of urban expansion on carbon storage in terrestrial ecosystems based on InVEST model and CA:A case study of Guangdong Province,China[J]. Geography and Geo-Information Science, 2016, 32(5):22-28.
[11]
Liang Y, Liu L, Huang J. Integrating the SD-CLUE-S and InVEST models into assessment of oasis carbon storage in northwestern China[J]. Plos One, 2017, 12(2):e0172494.
doi: 10.1371/journal.pone.0172494
[12]
Liang X, Guan Q, 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.
doi: 10.1016/j.compenvurbsys.2020.101569
[13]
Liu X P, Liang X, Li X, et al. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects[J]. Landscape and Urban Planning, 2017, 168:94-116.
doi: 10.1016/j.landurbplan.2017.09.019
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.
Ke X L, Pu K P, Yang B H, et al. Impacts of cultivated land protection on water retention fuction of ecosysteam:A case study in Wuhan[J]. Research of Soil and Water Conservation, 2018, 25(1):391-396.
[16]
Babbar D, Areendran G, Sahana M, et al. Assessment and prediction of carbon sequestration using Markov chain and InVEST model in Sariska Tiger Reserve,India[J]. Journal of Cleaner Production, 2021, 278:123333.
doi: 10.1016/j.jclepro.2020.123333
[17]
Sharp R, Douglass J, Wolny S, et al. InVEST 3.8.9 User’s Guide[Z]. The Natural Capital Project,Stanford University,University of Minnesota,the Nature Conservancy,and World Wildlife Fund, 2020.
Ke X L, Tang L P. Impact of cascading processes of urban expansion and cropland reclamation on the ecosystem of a carbon storage service in Hubei Province,China[J]. Acta Ecologica Sinica, 2019, 39(2):672-683.
[19]
Lyu R F, Mi L N, Zhang J M, et al. Modeling the effects of urban expansion on regional carbon storage by coupling SLEUTH-3r model and InVEST model[J]. Ecological Research, 2019, 34(3):380-393.
doi: 10.1111/1440-1703.1278
2022, Vol. 34 
), 赵娟1, 朱家田1, 刘雷1, 张平1,2(
