Vitousek, P. M., Mooney, H. A., Lubchenco, J. & Melillo, J. M. Human domination of earth’s ecosystems. Science 277, 494–499. https://doi.org/10.1126/science.277.5325.494 (1997).
Google Scholar
Yue, T. X., Fan, Z. M. & Liu, J. Y. Scenarios of land cover in China. Glob. Planet. Change 55, 317–342. https://doi.org/10.1016/j.gloplacha.2006.10.002 (2007).
Google Scholar
Ii, B. L. T., Lambin, E. F. & Reen Be Rg, A. The emergence of land change science for global environmental change and sustainability. Proc. Natl. Acad. Sci. USA 104, 20666–20671. https://doi.org/10.1073/pnas.0704119104 (2007).
Google Scholar
IPCC. 2006 IPCC Guidelines for National Greenhouse Gas Inventories—IPCC. https://www.ipcc.ch/report/2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/ (2006).
Gallant, K., Withey, P., Risk, D., van Kooten, G. C. & Spafford, L. Measurement and economic valuation of carbon sequestration in Nova Scotian wetlands. Ecol. Econ. 171, 106619. https://doi.org/10.1016/j.ecolecon.2020.10661 (2020).
Google Scholar
Deng, C. et al. Spatiotemporal dislocation of urbanization and ecological construction increased the ecosystem service supply and demand imbalance. J. Environ. Manag. 288, 112478. https://doi.org/10.1016/j.jenvman.2021.112478 (2021).
Google Scholar
Wang, J., Zhai, T., Lin, Y., Kong, X. & He, T. Spatial imbalance and changes in supply and demand of ecosystem services in China. Sci. Total Environ. 657, 781–791. https://doi.org/10.1016/j.scitotenv.2018.12.080 (2019).
Google Scholar
Long, R., Li, J., Chen, H., Zhang, L. & Li, Q. Embodied carbon dioxide flow in international trade: A comparative analysis based on China and Japan. J. Environ. Manag. 209, 371–381. https://doi.org/10.1016/j.jenvman.2017.12.067 (2018).
Google Scholar
Lv, Y., Liu, J., Cheng, J. & Andreoni, V. The persistent and transient total factor carbon emission performance and its economic determinants: Evidence from China’s province-level panel data. J. Clean. Prod. 316, 128198. https://doi.org/10.1016/j.jclepro.2021.128198 (2021).
Google Scholar
Wang, Y., Shataer, R., Zhang, Z., Zhen, H. & Xia, T. Evaluation and analysis of influencing factors of ecosystem service value change in Xinjiang under different land use types. Water 14, 1424. https://doi.org/10.3390/w14091424 (2022).
Google Scholar
Zhang, Y. et al. How can an ecological compensation threshold be determined? A discriminant model integrating the minimum data approach and the most appropriate land use scenarios. Sci. Total Environ. 852, 158377. https://doi.org/10.1016/j.scitotenv.2022.158377 (2022).
Google Scholar
Shi, M. et al. Cropland expansion mitigates the supply and demand deficit for carbon sequestration service under different scenarios in the future—the case of Xinjiang. Agriculture 12, 1182. https://doi.org/10.3390/agriculture12081182 (2022).
Google Scholar
Yuan, K., Li, F., Yang, H. & Wang, Y. The influence of land use change on ecosystem service value in Shangzhou district. Int. J. Environ. Res. Public. Health 16, 1321. https://doi.org/10.3390/ijerph16081321 (2019).
Google Scholar
Millennium Ecosystem Assessment (MEA). Ecosystems and Human Well-Being: Multiscale Assessments. https://www.millenniu-massessment.org/en/Multiscale.html (Island Press, 2005).
Liu, J. Y., Liu, M. L., Zhuang, D. F., Zhang, Z. X. & Deng, X. Z. Study on spatial pattern of land-use change in China during 1995–2000. Sci. China Ser. Earth Sci. 46, 373–384. https://doi.org/10.1360/03yd9033 (2003).
Google Scholar
Lambin, E. F. & Meyfroidt, P. Land use transitions: Socio-ecological feedback versus socio-economic change. Land Use Policy 27, 108–118. https://doi.org/10.1016/j.landusepol.2009.09.003 (2010).
Google Scholar
Long, H., Qu, Y., Tu, S., Zhang, Y. & Jiang, Y. Development of land use transitions research in China. J. Geogr. Sci. 30, 1195–1214. https://doi.org/10.1007/s11442-020-1777-9 (2020).
Google Scholar
Portela, R. & Rademacher, I. A dynamic model of patterns of deforestation and their effect on the ability of the Brazilian Amazonia to provide ecosystem services. Ecol. Model. 143, 115–146. https://doi.org/10.1016/S0304-3800(01)00359-3 (2001).
Google Scholar
Yin, D., Li, X., Li, G., Zhang, J. & Yu, H. Spatio-temporal evolution of land use transition and its eco-environmental effects: A case study of the Yellow River Basin, China. Land 9, 514. https://doi.org/10.3390/land9120514 (2020).
Google Scholar
Alkimim, A. & Clarke, K. C. Land use change and the carbon debt for sugarcane ethanol production in Brazil. Land Use Policy 72, 65–73. https://doi.org/10.1016/j.landusepol.2017.12.039 (2018).
Google Scholar
Wang, J. & Zhou, W. Ecosystem service flows: Recent progress and future perspectives. Acta Ecol. Sin. 39, 4213–4222. https://doi.org/10.5846/stxb201807271605 (2019).
Google Scholar
Krozer, Y., Coenen, F., Hanganu, J., Lordkipanidze, M. & Sbarcea, M. Towards innovative governance of nature areas. Sustainability 12, 10624. https://doi.org/10.3390/su122410624 (2020).
Google Scholar
Pan, X., Xu, L., Yang, Z. & Yu, B. Payments for ecosystem services in China: Policy, practice, and progress. J. Clean. Prod. 158, 200–208. https://doi.org/10.1016/j.jclepro.2017.04.127 (2017).
Google Scholar
Su, K. et al. The establishment of a cross-regional differentiated ecological compensation scheme based on the benefit areas and benefit levels of sand-stabilization ecosystem service. J. Clean. Prod. 270, 122490. https://doi.org/10.1016/j.jclepro.2020.122490 (2020).
Google Scholar
Zhai, T., Zhang, D. & Zhao, C. How to optimize ecological compensation to alleviate environmental injustice in different cities in the Yellow River Basin? A case of integrating ecosystem service supply, demand and flow. Sustain. Cities Soc. 75, 103341. https://doi.org/10.1016/j.scs.2021.103341 (2021).
Google Scholar
Zhai, T. et al. Did improvements of ecosystem services supply-demand imbalance change environmental spatial injustices?. Ecol. Indic. 111, 106068. https://doi.org/10.1016/j.ecolind.2020.106068 (2020).
Google Scholar
Chen, W. et al. Land use transitions and the associated impacts on ecosystem services in the Middle Reaches of the Yangtze River Economic Belt in China based on the geo-informatic Tupu method. Sci. Total Environ. 701, 134690. https://doi.org/10.1016/j.scitotenv.2019.134690 (2020).
Google Scholar
Zheng, W., Ke, X., Xiao, B. & Zhou, T. Optimising land use allocation to balance ecosystem services and economic benefits—A case study in Wuhan, China. J. Environ. Manag. 248, 109306. https://doi.org/10.1016/j.jenvman.2019.109306 (2019).
Google Scholar
Li, Z., Deng, X., Jin, G., Mohmmed, A. & Arowolo, A. O. Tradeoffs between agricultural production and ecosystem services: A case study in Zhangye, Northwest China. Sci. Total Environ. 707, 136032. https://doi.org/10.1016/j.scitotenv.2019.136032 (2020).
Google Scholar
Raudsepp-Hearne, C., Peterson, G. D. & Bennett, E. M. Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. Proc. Natl. Acad. Sci. USA. 107, 5242–5247. https://doi.org/10.1073/pnas.0907284107 (2010).
Google Scholar
Yuan, B. et al. Spatiotemporal change detection of ecological quality and the associated affecting factors in Dongting Lake Basin, based on RSEI. J. Clean. Prod. 302, 126995. https://doi.org/10.1016/j.jclepro.2021.126995 (2021).
Google Scholar
An, M. et al. Spatiotemporal change of ecologic environment quality and human interaction factors in three gorges ecologic economic corridor, based on RSEI. Ecol. Indic. 141, 109090. https://doi.org/10.1016/j.ecolind.2022.109090 (2022).
Google Scholar
Liu, W., Yan, Y., Wang, D. & Ma, W. Integrate carbon dynamics models for assessing the impact of land use intervention on carbon sequestration ecosystem service. Ecol. Indic. 91, 268–277. https://doi.org/10.1016/j.ecolind.2018.03.087 (2018).
Google Scholar
Adelisardou, F. et al. 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. 19, 5929–5944. https://doi.org/10.1007/s13762-021-03676-6 (2021).
Google Scholar
Yang, F. et al. Taklimakan desert carbon-sink decreases under climate change. Sci. Bull. 65, 431–433. https://doi.org/10.1016/j.scib.2019.12.022 (2020).
Google Scholar
Huang, L., Liu, J., Shao, Q. & Xu, X. Carbon sequestration by forestation across China: Past, present, and future. Renew. Sustain. Energy Rev. 16, 1291–1299. https://doi.org/10.1016/j.rser.2011.10.004 (2012).
Google Scholar
Hong, C. et al. Land-use emissions embodied in international trade. Science 376, 597–603. https://doi.org/10.1126/science.abj1572 (2022).
Google Scholar
Zhu, E. et al. Carbon emissions induced by land-use and land-cover change from 1970 to 2010 in Zhejiang, China. Sci. Total Environ. 646, 930–939. https://doi.org/10.1016/j.scitotenv.2018.07.317 (2019).
Google Scholar
Xiao, D., Niu, H., Guo, J., Zhao, S. & Fan, L. Carbon storage change analysis and emission reduction suggestions under land use transition: A case study of Henan province, China. Int. J. Environ. Res. Public. Health 18, 1844. https://doi.org/10.3390/ijerph18041844 (2021).
Google Scholar
Boisvenue, C., Bergeron, Y., Bernier, P. & Peng, C. Simulations show potential for reduced emissions and carbon stocks increase in boreal forests under ecosystem management. Carbon Manag. 3, 553–568. https://doi.org/10.4155/CMT.12.57 (2012).
Google Scholar
Heimann, M. & Reichstein, M. Terrestrial ecosystem carbon dynamics and climate feedbacks. Nature 451, 289–292. https://doi.org/10.1038/nature06591 (2008).
Google Scholar
Li, T., Li, J. & Wang, Y. Carbon sequestration service flow in the Guanzhong-Tianshui economic region of China: How it flows, what drives it, and where could be optimized?. Ecol. Indic. 96, 548–558. https://doi.org/10.1016/j.ecolind.2018.09.040 (2019).
Google Scholar
Yan, X. et al. An overview of distribution characteristics and formation mechanisms in global arid areas. Adv. Earth Sci. 34, 826–841. https://doi.org/10.11867/j.issn.1001-8166.2019.08.0826 (2019).
Google Scholar
Abulizi, A. et al. Land-use change and its effects in Charchan Oasis, Xinjiang, China. Land Degrad. Dev. 28, 106–115. https://doi.org/10.1002/ldr.2530 (2017).
Google Scholar
Zhang, Z. et al. Spatiotemporal characteristics in ecosystem service value and its interaction with human activities in Xinjiang, China. Ecol. Indic. 110, 105826. https://doi.org/10.1016/j.ecolind.2019.105826 (2020).
Google Scholar
Xie, L., Wang, H. & Liu, S. The ecosystem service values simulation and driving force analysis based on land use/land cover: A case study in inland rivers in arid areas of the Aksu River Basin, China. Ecol. Indic. 138, 108828. https://doi.org/10.1016/j.ecolind.2022.108828 (2022).
Google Scholar
Wang, Z. et al. Dynamic simulation of land use change and assessment of carbon storage based on climate change scenarios at the city level: A case study of Bortala, China. Ecol. Indic. 134, 108499. https://doi.org/10.1016/j.ecolind.2021.108499 (2022).
Google Scholar
Shi, M. et al. Trade-offs and synergies of multiple ecosystem services for different land use scenarios in the Yili River Valley, China. Sustainability 13, 1577. https://doi.org/10.3390/su13031577 (2021).
Google Scholar
Wang, C., Zhen, L., Bingzhen, D. U. & Sun, C. Assessment of the impact of Grain for Green project on farmers’ livelihood in the Loess Plateau. Chin. J. Eco-Agric. 22, 850–858. https://doi.org/10.3724/SP.J.1011.2014.30944 (2014).
Google Scholar
Yang, H., Mu, S. & Li, J. Effects of ecological restoration projects on land use and land cover change and its influences on territorial NPP in Xinjiang, China. CATENA 115, 85–95. https://doi.org/10.1016/j.catena.2013.11.020 (2014).
Google Scholar
Bahtebay, J., Zhang, F., Ariken, M., Chan, N. W. & Tan, M. L. Evaluation of the coordinated development of urbanization-resources-environment from the incremental perspective of Xinjiang. China. J. Clean. Prod. 325, 129309. https://doi.org/10.1016/j.jclepro.2021.129309 (2021).
Google Scholar
Chen, J. et al. County-level CO2 emissions and sequestration in China during 1997–2017. Sci. Data 7, 391. https://doi.org/10.1038/s41597-020-00736-3 (2020).
Google Scholar
Zhu, H. & Li, X. Discussion on the index method of regional land use change. Acta Geogr. Sin. 58, 643–650. https://doi.org/10.3321/j.issn:0375-5444.2003.05.001 (2003).
Google Scholar
Li, Y., Cao, Z., Long, H., Liu, Y. & Li, W. Dynamic analysis of ecological environment combined with land cover and NDVI changes and implications for sustainable urban–rural development: The case of Mu Us Sandy Land, China. J. Clean. Prod. 142, 697–715. https://doi.org/10.1016/j.jclepro.2016.09.011 (2017).
Google Scholar
Zhou, Q., Li, B. & Kurban, A. Trajectory analysis of land cover change in arid environment of China. Int. J. Remote Sens. 29, 1093–1107. https://doi.org/10.1080/01431160701355256 (2008).
Google Scholar
Zhang, F. & Rusuli, Y. Spatio-temporal variation of ecosystem service value based on LUCC trajectories: A case study of Bosten Lake Watershed. J. Beijing For. Univ. 43, 88–99. https://doi.org/10.12171/j.1000-1522.20210017 (2021).
Google Scholar
Keller, A. A., Fournier, E. & Fox, J. Minimizing impacts of land use change on ecosystem services using multi-criteria heuristic analysis. J. Environ. Manag. 156, 23–30. https://doi.org/10.1016/j.jenvman.2015.03.017 (2015).
Google Scholar
Li, K. et al. 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. 39, 100641. https://doi.org/10.1016/j.envdev.2021.100641 (2021).
Google Scholar
Tang, X. et al. Carbon pools in China’s terrestrial ecosystems: New estimates based on an intensive field survey. Proc. Natl. Acad. Sci. USA. 115, 4021–4026. https://doi.org/10.1073/pnas.1700291115 (2018).
Google Scholar
Yang, F. et al. Impact of differences in soil temperature on the desert carbon sink. Geoderma 379, 114636. https://doi.org/10.1016/j.geoderma.2020.114636 (2020).
Google Scholar
Xiang, M. et al. Spatio-temporal evolution and driving factors of carbon storage in the Western Sichuan Plateau. Sci. Rep. 12, 8114. https://doi.org/10.1038/s41598-022-12175-8 (2022).
Google Scholar
de Groot, R. S., Wilson, M. A. & Boumans, R. M. J. A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol. Econ. 41, 393–408. https://doi.org/10.1016/S0921-8009(02)00089-7 (2002).
Google Scholar
Chen, J., Xue, M., Su, X. & Gao, J. Spatial transfer of regional ecosystem service in Nanjing City. Acta Ecol. Sin. 34, 5087–5095. https://doi.org/10.5846/stxb201308162095 (2014).
Google Scholar
Hu, X. et al. Carbon sequestration benefits of the grain for Green Program in the hilly red soil region of southern China. Int. Soil Water Conserv. Res. 9, 271–278. https://doi.org/10.1016/j.iswcr.2020.11.005 (2021).
Google Scholar
Yao, J. et al. Recent climate and hydrological changes in a mountain–basin system in Xinjiang, China. Earth-Sci. Rev. 226, 103957. https://doi.org/10.1016/j.earscirev.2022.103957 (2022).
Google Scholar
Li, J., Zuo, Q. & Ma, J. Analysis of spatial and temporal evolution characteristics of water-socioeconomic-ecosystem in Xinjiang. J. Beijing Norm. Univ. Sci. 56, 591–599. https://doi.org/10.12202/j.0476-0301.2020170 (2020).
Google Scholar
Chen, X., Chang, C., Bao, A., Wu, S. & Luo, G. Spatial pattern and characteristics of land cover change in Xinjiang since past 40 years of the economic reform and opening up. ARID LAND Geogr. 43, 1–11. https://doi.org/10.12118/j.issn.1000-6060.2020.01.01 (2020).
Google Scholar
Han, B. et al. Research progress and key issues of territory consolidation under the target of rural revitalization. J. Nat. Resour. 36, 3007–3030. https://doi.org/10.31497/zrzyxb.20211202 (2021).
Google Scholar
Ziyuan, C. et al. Carbon emissions index decomposition and carbon emissions prediction in Xinjiang from the perspective of population-related factors, based on the combination of STIRPAT model and neural network. Environ. Sci. Pollut. Res. 29, 31781–31796. https://doi.org/10.1007/s11356-021-17976-4 (2022).
Google Scholar
Wang, C. et al. Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang. Renew. Sustain. Energy Rev. 67, 51–61. https://doi.org/10.1016/j.rser.2016.09.006 (2017).
Google Scholar
Ma, C., Chen, Q., Hu, F., Li, S. & Cong, J. Research characteristic of carbon emissions calculation in Xinjiang. Resour. Dev. Mark. 36, 233–240+267. https://doi.org/10.3969/j.issn.1005-8141.2020.03.002 (2020).
Google Scholar
Qin, Z. et al. Natural climate solutions for China: The last mile to carbon neutrality. Adv. Atmos. Sci. 38, 889–895. https://doi.org/10.1007/s00376-021-1031-0 (2021).
Google Scholar
Kong, R. et al. Increasing carbon storage in subtropical forests over the Yangtze River basin and its relations to the major ecological projects. Sci. Total Environ. 709, 136163. https://doi.org/10.1016/j.scitotenv.2019.136163 (2020).
Google Scholar
Chang, J. et al. Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands. Nat. Commun. 12, 118. https://doi.org/10.1038/s41467-020-20406-7 (2021).
Google Scholar
Wang, X. & Nuppenau, E.-A. Modelling payments for ecosystem services for solving future water conflicts at spatial scales: The Okavango River Basin example. Ecol. Econ. 184, 106982. https://doi.org/10.1016/j.ecolecon.2021.106982 (2021).
Google Scholar
Source: Ecology - nature.com
