Regional Carbon Storage Dynamics Driven by Tea Plantation Expansion: Insights from Meitan County, China
Abstract
:1. Introduction
2. Study Area
3. Materials and Methods
3.1. Research Methods
3.1.1. Land-Use Spatiotemporal Change Analysis
3.1.2. Future Scenario Simulations of LUCC
3.1.3. InVEST Model
3.2. Data Sources
4. Results
4.1. LUCC Features
4.2. Characteristics of Carbon Storage Changes
4.3. Future Scenario Simulations
5. Discussion
5.1. Comparison of Carbon Storage Changes
5.2. Policy Recommendations
5.3. Shortcomings and Prospects
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Friedlingstein, P.; O’Sullivan, M.; Jones, M.W.; Andrew, R.M.; Gregor, L.; Hauck, J.; Le Quéré, C.; Luijkx, I.T.; Olsen, A.; Peters, G.P.; et al. Global carbon budget 2022. Earth Syst. Sci. Data 2022, 14, 4811–4900. [Google Scholar] [CrossRef]
- Houghton, R.A. Aboveground forest biomass and the global carbon balance. Glob. Change Biol. 2005, 11, 945–958. [Google Scholar] [CrossRef]
- Pan, Y.; Birdsey, R.A.; Phillips, O.L.; Houghton, R.A.; Fang, J.; Kauppi, P.E.; Keith, H.; Kurz, W.A.; Ito, A.; Lewis, S.L.; et al. The enduring world forest carbon sink. Nature 2024, 631, 563–569. [Google Scholar] [CrossRef] [PubMed]
- Wu, X.; Shen, C.; Shi, L.; Wan, Y.; Ding, J.; Wen, Q. Spatio-temporal evolution characteristics and simulation prediction of carbon storage: A case study in Sanjiangyuan Area, China. Ecol. Inform. 2024, 80, 102485. [Google Scholar] [CrossRef]
- Intergovernmental Panel on Climate Change (IPCC). 2019 Refinement to the 2006 IPCC guidelines for national greenhouse gas inventories. Agric. For. Other Land Use 2019, 4, 824. [Google Scholar]
- Li, L.; Xu, E. Scenario analysis and relative importance indicators for combined impact of climate and land-use change on annual ecosystem services in the Karst mountainous region. Ecol. Indic. 2023, 147, 109991. [Google Scholar] [CrossRef]
- Lapola, D.M.; Pinho, P.; Barlow, J.; Aragão, L.E.; Berenguer, E.; Carmenta, R.; Liddy, H.M.; Seixas, H.; Silva, C.V.; Silva-Junior, C.H.; et al. The drivers and impacts of Amazon forest degradation. Science 2023, 379, eabp8622. [Google Scholar] [CrossRef]
- Huang, L. A review on the climatic regulation effects of afforestation and its impact mechanisms. Acta Ecol. Sin. 2021, 41, 469–478. [Google Scholar]
- Luo, D.; Zhou, Z.F.; Chen, Q.; Zhang, L.; Wu, L.; Wu, T.Y. Responses of carbon storage to land use pattern in karst area: A case study of Nanbei Panjiang River Basin. Acta Ecol. Sin. 2023, 43, 3500–3516. [Google Scholar]
- Liu, S.; Yao, X.; Zhao, D.; Lu, L. Evaluation of the ecological benefits of tea gardens in Meitan County, China, using the InVEST model. Environ. Dev. Sustain. 2021, 23, 7140–7155. [Google Scholar] [CrossRef]
- Liu, W.Y.; Chiang, C.Y.; Yap, J.L.; Lin, C.C. Assessing the ecosystem service values of tea plantations using conventional and organic farming methods: Is organic farming always better? Ecol. Indic. 2024, 158, 111355. [Google Scholar] [CrossRef]
- Ouyang, Z.; Zheng, H.; Xiao, Y.; Polasky, S.; Liu, J.; Xu, W.; Wang, Q.; Zhang, L.; Xiao, Y.; Rao, E.; et al. Improvements in ecosystem services from investments in natural capital. Science 2016, 352, 1455–1459. [Google Scholar] [CrossRef] [PubMed]
- Liang, X.; Guan, Q.; Clarke, K.C.; Liu, S.; Wang, B.; Yao, Y. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China. Comput. Environ. Urban Syst. 2021, 85, 101569. [Google Scholar] [CrossRef]
- Qiao, X.; Li, Z.; Lin, J.; Wang, H.; Zheng, S.; Yang, S. Assessing current and future soil erosion under changing land use based on InVEST and FLUS models in the Yihe River Basin, North China. Int. Soil Water Conserv. Res. 2024, 12, 298–312. [Google Scholar] [CrossRef]
- Hwang, J.; Choi, Y.; Kim, Y.; Ol, L.N.; Yoo, Y.J.; Cho, H.J.; Sun, Z.; Jeon, S. Analysis of the effect of environmental protected areas on land-use and carbon storage in a megalopolis. Ecol. Indic. 2021, 133, 108352. [Google Scholar] [CrossRef]
- Jiang, W.; Deng, Y.; Tang, Z.; Lei, X.; Chen, Z. Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models. Ecol. Model. 2017, 345, 30–40. [Google Scholar] [CrossRef]
- Babbar, D.; Areendran, G.; Sahana, M.; Sarma, K.; Raj, K.; Sivadas, A. Assessment and prediction of carbon sequestration using Markov chain and InVEST model in Sariska Tiger Reserve, India. J. Clean. Prod. 2021, 278, 123333. [Google Scholar] [CrossRef]
- Du, S.; Zhou, Z.; Huang, D.; Zhang, F.; Deng, F.; Yang, Y. The response of carbon stocks to land use/cover change and a vulnerability multi-scenario analysis of the Karst region in southern China based on PLUS-InVEST. Forests 2023, 14, 2307. [Google Scholar] [CrossRef]
- Tian, L.; Tao, Y.; Fu, W.; Li, T.; Ren, F.; Li, M. Dynamic simulation of land use/cover change and assessment of forest ecosystem carbon storage under climate change scenarios in Guangdong Province, China. Remote Sens. 2022, 14, 2330. [Google Scholar] [CrossRef]
- Ma, X.Y.; Xu, Y.F.; Sun, Q.; Liu, W.J.; Qi, W. Contributing to carbon neutrality targets: A scenario simulation and pattern optimization of land use in Shandong Province based on the PLUS model. Sustainability 2024, 16, 5180. [Google Scholar] [CrossRef]
- Zhang, S.; Sun, C.; Zhang, Y.; Hu, M.; Shen, X. Exploring the spatiotemporal changes and driving forces of ecosystem services of Zhejiang Coasts, China, under sustainable development goals. Chin. Geogr. Sci. 2024, 34, 647–661. [Google Scholar] [CrossRef]
- Hu, X.; Li, Z.; Chen, J.; Nie, X.; Liu, J.; Wang, L.; Ning, K. Carbon sequestration benefits of the Grain for Green Program in the hilly red soil region of southern China. Int. Soil Water Conserv. Res. 2021, 9, 271–278. [Google Scholar] [CrossRef]
- Liu, G.; Zhao, Z. Analysis of carbon storage and its contributing factors—A case study in the Loess Plateau (China). Energies 2018, 11, 1596. [Google Scholar] [CrossRef]
- Zhao, Z.; Liu, G.; Mou, N.; Xie, Y.; Xu, Z.; Li, Y. Assessment of carbon storage and its influencing factors in Qinghai-Tibet Plateau. Sustainability 2018, 10, 1864. [Google Scholar] [CrossRef]
- Nie, X.; Lu, B.; Chen, Z.; Yang, Y.; Chen, S.; Chen, Z.; Wang, H. Increase or decrease? Integrating the CLUMondo and InVEST models to assess the impact of the implementation of the Major Function Oriented Zone planning on carbon storage. Ecol. Indic. 2020, 118, 106708. [Google Scholar] [CrossRef]
- Wang, C.; Yang, K.; Yang, W.; Qiang, H.; Xue, H.; Lu, B.; Zhou, P. R-MFNet: Analysis of urban carbon stock change against the background of land-use change based on a residual multi-module fusion network. Remote Sens. 2023, 15, 2823. [Google Scholar] [CrossRef]
- Adelisardou, F.; Zhao, W.; Chow, R.; Mederly, P.; Minkina, T.; Schou, J.S. Spatiotemporal change detection of carbon storage and sequestration in an arid ecosystem by integrating Google Earth Engine and InVEST (the Jiroft plain, Iran). Int. J. Environ. Sci. Technol. 2022, 1–16. [Google Scholar] [CrossRef]
- Li, K.; Cao, J.; Adamowski, J.F.; Mederly, P.; Minkina, T.; Schou, J.S. Assessing the effects of ecological engineering on spatiotemporal dynamics of carbon storage from 2000 to 2016 in the Loess Plateau area using the InVEST model: A case study in Huining County, China. Environ. Dev. 2021, 39, 100641. [Google Scholar] [CrossRef]
- Wu, L.; Yang, S.; Liu, X.; Luo, Y.; Zhou, X.; Zhao, H. Response analysis of land use change to the degree of human activities in Beiluo River basin since 1976. Acta Geogr. Sin. 2014, 69, 54–63. [Google Scholar]
- Peng, J.; Cai, Y.; Wang, X. Assessment on land use/cover change in karst areas based on landscape ecology: A case study at Maotiaohe River Basin, Guizhou, China. Carsologica Sin. 2007, 2, 137–143. [Google Scholar]
- Xu, Y.; Yu, L.; Peng, D.; Zhao, J.; Cheng, Y.; Liu, X.; Li, W.; Meng, R.; Xu, X.; Gong, P. Annual 30-m land use/land cover maps of China for 1980–2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm. Sci. China Earth Sci. 2020, 63, 1390–1407. [Google Scholar] [CrossRef]
- Gao, H.; Han, H.; Zhang, C.; Wang, H. The impact of land use change on carbon storage in the Guizhou section of the Wujiang River Basin from 2000 to 2010. J. Sichuan Agric. Univ. 2016, 34, 48–53+84. [Google Scholar]
- Li, J.; Gong, J.; Guldmann, J.M.; Li, S.; Zhu, J. Carbon dynamics in the northeastern Qinghai–Tibetan Plateau from 1990 to 2030 using Landsat land use/cover change data. Remote Sens. 2020, 12, 528. [Google Scholar] [CrossRef]
- Li, M.; Ding, G. Research on carbon storage of major forest types in Guizhou Qiandongnan. J. Cent. South Univ. For. Technol. 2013, 33, 119–124. [Google Scholar]
- Li, Y.; Luo, H. Temporal and spatial evolution of carbon storage in typical counties in karst areas of central Guizhou and multi-scenario simulation prediction: A case study of Puding County. Environ. Sci. 2024, 45, 961–973. [Google Scholar]
- Zhang, S.; Bai, X.; Wang, S.; Qin, L.; Tian, Y.; Luo, G.; Li, Y. Assessment of ecosystem services in typical rocky desertification areas based on InVEST model: A case study of Qinglong County. J. Earth Environ. 2014, 5, 328–338. [Google Scholar]
- Shu-Qi, H.; Da-Fang, W.; Yue-Ling, P.; Jin-Yao, L.; Zhou, P. A study on the spatiotemporal dynamics of land cover change and carbon storage in the northern Gulf Economic Zone of Guangxi based on the InVEST model. Atmosphere 2024, 15, 1332. [Google Scholar] [CrossRef]
- Tang, L.; Ke, X.; Zhou, T.; Zheng, W.; Wang, L. Impacts of cropland expansion on carbon storage: A case study in Hubei, China. J. Environ. Manag. 2020, 265, 110515. [Google Scholar] [CrossRef]
- Yue, C.; Ciais, P.; Houghton, R.A.; Nassikas, A.A. Contribution of land use to the interannual variability of the land carbon cycle. Nat. Commun. 2020, 11, 3170. [Google Scholar] [CrossRef]
- Sha, Z.; Bai, Y.; Lan, H.; Liu, X.; Xie, Y. Can more carbon be captured by grasslands? A case study of Inner Mongolia, China. Sci. Total Environ. 2020, 723, 138085. [Google Scholar] [CrossRef]
- Nazir, M.J.; Nazir, M.J.; Li, G.; Nazir, M.; Zulfiqar, F.; Siddique, K.H.; Iqbal, B.; Du, D. Harnessing soil carbon sequestration to address climate change challenges in agriculture. Soil Tillage Res. 2024, 237, 105959. [Google Scholar] [CrossRef]
- Yang, W.; Pan, J. How do trade-offs between ecological construction and urbanization affect regional carbon balance? A case study from China’s Yellow River Basin. Catena 2024, 247, 108534. [Google Scholar] [CrossRef]
- Tong, H.; Xia, E.; Sun, C.; Yan, K.; Li, J.; Huang, J. Construction and comprehensive evaluation of an index system for climate-smart agricultural development in China. J. Clean. Prod. 2024, 469, 143216. [Google Scholar] [CrossRef]
- Bhagat, R.; Walia, S.S.; Sharma, K.; Singh, R.; Singh, G.; Hossain, A. The integrated farming system is an environmentally friendly and cost-effective approach to the sustainability of agri-food systems in the modern era of the changing climate: A comprehensive review. Food Energy Secur. 2024, 13, e534. [Google Scholar] [CrossRef]
Land Type | Cultivated Land | Forest Land | Grass Land | Water Area | Construction Land | Unused Land |
---|---|---|---|---|---|---|
Weight | 0.176 | 0.062 | 0.02 | 0.238 | 0.491 | 0.001 |
NDS | SDS | EDS | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A | B | C | D | E | A | B | C | D | E | A | B | C | D | E | |
A | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 |
B | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 |
C | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 |
D | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 |
E | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 |
Type | Definition |
---|---|
Cultivated land | Land used for the cultivation of crops, including both dry and irrigated fields. |
Forest land | Areas covered by forests, including natural forests and plantations, used primarily for timber production, conservation, or other ecological functions. |
Grass land | Refers to various types of land primarily covered by herbaceous plants, with a vegetation cover of more than 5%. |
Water area | Surface water bodies such as rivers, lakes, reservoirs, wetlands, and land used for hydraulic facilities. |
Construction land | Land used for urban and rural construction, including residential, industrial, and commercial areas, as well as transportation infrastructure. |
Unused land | construction purposes, often due to natural conditions or land-use restrictions. |
Data Type | Data Names | Data Sources |
---|---|---|
Natural factor | DEM | Geospatial Data Clound http://www.gscloud.cn (accessed on 17 June 2024) |
Slope | DEM extraction obtained from Geospatial Data Cloud http://www.gscloud.cn (accessed on 17 June 2024) | |
Aspect | ||
Soil type | Resource and Environment Science and Data Center http://www.resdc.cn (accessed on 20 June 2024) | |
NDVI | ||
Annual precipitation | ||
Mean annual temperature | ||
Social factor | GDP | Resource and Environment Science and Data Center http://www.resdc.cn (accessed on 17 June 2024) |
Night-time light intensity | ||
Population density | Worldpop https://www.worldpop.org (accessed on 23 June 2024) | |
Distance to highways | National Geomatics Center of China https://www.ngcc.cn (accessed on 23 June 2024) | |
Distance to national roads | ||
Distance to provincial roads | ||
Distance to county roads | ||
Distance to township roads | ||
Distance to the nearest government location | ||
Distance to the county center |
Type | Df-above | Df-below | Df-soil | Df-dead |
---|---|---|---|---|
Cultivated land | 38.9 | 7.3 | 89.18 | 1 |
Forest land | 45.08 | 18.03 | 171.84 | 7.8 |
Grass land | 3.6 | 24.4 | 129.6 | 0 |
Water area | 0 | 0 | 0 | 0 |
Construction land | 0 | 0 | 111.26 | 0 |
Unused land | 0.74 | 0.13 | 69.92 | 0 |
Land Type | 2000 | 2005 | 2010 | 2015 | 2020 |
---|---|---|---|---|---|
Cultivated land | 479.84 | 475.48 | 473.42 | 470.25 | 461.79 |
Forest land | 1347.7 | 1352.03 | 1361.95 | 1362.20 | 1355.75 |
Grass land | 31.9 | 29.67 | 15.86 | 15.79 | 14.36 |
Water area | 3.92 | 3.96 | 11.65 | 10.91 | 16.83 |
Construction land | 4.51 | 4.64 | 5.09 | 7.93 | 19.22 |
Unused land | 0.07 | 0.04 | \ | \ | \ |
Year | Tea Plantation Area (km2) | Tea Plantation Output Value (Million USD) | Forest Land Area (km2) |
---|---|---|---|
2000 | 18.67 | 0.13 | 1347.7 |
2005 | 65.20 | 0.44 | 1352.03 |
2010 | 190.08 | 1.28 | 1361.95 |
2015 | 376.75 | 3.95 | 1362.2 |
2020 | 404.95 | 8.52 | 1355.75 |
Land Type | 2000 | NDS | SDS | EDS |
---|---|---|---|---|
Cultivated land | 631.09 | 596.34 | 596.34 | 585.92 |
Forest land | 3285.55 | 3230.87 | 3286.1 | 3225.72 |
Grass land | 22.81 | 20.46 | 23.3 | 17.86 |
Construction land | 21.4 | 22.59 | 23.58 | 35.61 |
Total | 3960.85 | 3870.26 | 3929.32 | 3865.11 |
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Share and Cite
Zuo, R.; Ma, Y.; Tang, M.; Luo, H.; Li, J.; Liao, T.; Gong, Y.; Zhang, S.; Gong, J.; Yi, Y. Regional Carbon Storage Dynamics Driven by Tea Plantation Expansion: Insights from Meitan County, China. Land 2025, 14, 227. https://doi.org/10.3390/land14020227
Zuo R, Ma Y, Tang M, Luo H, Li J, Liao T, Gong Y, Zhang S, Gong J, Yi Y. Regional Carbon Storage Dynamics Driven by Tea Plantation Expansion: Insights from Meitan County, China. Land. 2025; 14(2):227. https://doi.org/10.3390/land14020227
Chicago/Turabian StyleZuo, Renhui, Yan Ma, Ming Tang, Hao Luo, Junqin Li, Tao Liao, Yuanfang Gong, Shunfu Zhang, Jiyi Gong, and Yin Yi. 2025. "Regional Carbon Storage Dynamics Driven by Tea Plantation Expansion: Insights from Meitan County, China" Land 14, no. 2: 227. https://doi.org/10.3390/land14020227
APA StyleZuo, R., Ma, Y., Tang, M., Luo, H., Li, J., Liao, T., Gong, Y., Zhang, S., Gong, J., & Yi, Y. (2025). Regional Carbon Storage Dynamics Driven by Tea Plantation Expansion: Insights from Meitan County, China. Land, 14(2), 227. https://doi.org/10.3390/land14020227