Trade-Offs and Synergies of Multiple Ecosystem Services for Different Land Use Scenarios in the Yili River Valley, China

Sustainability - Tập 13 Số 3 - Trang 1577
Mingjie Shi1, Hongqi Wu1, Xin Fan2, Hongtao Jia1, Tong Dong1, Panxing He1, Muhammad Fahad Baqa3,4, Jiang Ping-an1
1College of Grass and Environmental Sciences, Xinjiang Agricultural University, Urumqi 830000, China
2School of Public Administration, China University of Geosciences (Wuhan), Wuhan, 430074, China
3Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
4College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Tóm tắt

Environmental managers and policymakers increasingly discuss trade-offs between ecosystem services (ESs). However, few studies have used nonlinear models to provide scenario-specific land-use planning. This study determined the effects of different future land use/land cover (LULC) scenarios on ESs in the Yili River Valley, China, and analyzed the trade-offs and synergistic response characteristics. We simulated land-use changes in the Yili River Valley during 2020–2030 under three different scenarios using a patch-generating land-use simulation (PLUS) model—business as usual (BAU), economic development (ED), and ecological conservation (EC). Subsequently, we evaluated the water yield (WY), carbon storage (CS), soil retention (SR), and nutrient export (NE) ESs by combining the PLUS and integrated valuation of ecosystem services and trade-offs (InVEST) models, thus exploring multiple trade-offs among these four ESs at a regional scale. For the BAU scenario, there are some synergistic effects between WY and SR in the Yili River Valley, in addition to significant trade-off effects between CS and NE. For the ED scenario, the rapid expansion of cropland and constructed land is at the expense of forested grassland, leading to a significant decline in ESs. For the EC scenario, the model predicted that the cumulative regional net future carbon storage, cumulative water retention, and cumulative soil conservation would all increase due to ecological engineering and the revegetation of riparian zones and that formerly steep agricultural land can be effective in improving ESs. Meanwhile, the trade-off effect would be significantly weakened between CS and NE. These results can inform decision makers on specific sites where ecological engineering is implemented. Our findings can enhance stakeholders’ understanding of the interactions between ESs indicators in different scenarios.

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Tài liệu tham khảo

Zheng, 2019, Realizing the values of natural capital for inclusive, sustainable development: Informing China’s new ecological development strategy, Proc. Natl. Acad. Sci. USA, 116, 8623, 10.1073/pnas.1819501116

Costanza, 1996, The total value of the world’s ecosystem services and natural capital, Nature, 387, 253, 10.1038/387253a0

Guerry, 2015, Natural capital and ecosystem services informing decisions: From promise to practice, Proc. Natl. Acad. Sci. USA, 112, 7348, 10.1073/pnas.1503751112

Gao, 2019, Suitability of regional development based on ecosystem service benefits and losses: A case study of the Yangtze River Delta urban agglomeration, China, Ecol. Indic., 107, 105579, 10.1016/j.ecolind.2019.105579

Danilo, 2018, Novel perspectives on bat insectivory highlight the value of this ecosystem service in farmland: Research frontiers and management implications, Agric. Ecosyst. Environ., 266, 31, 10.1016/j.agee.2018.07.024

Fu, 2018, Scenario analysis of ecosystem service changes and interactions in a mountain-oasis-desert system: A case study in Altay Prefecture, China, Sci. Rep., 8, 12939, 10.1038/s41598-018-31043-y

Deng, 2016, A review on trade-off analysis of ecosystem services for sustainable land-use management, J. Geogr. Sci., 26, 953, 10.1007/s11442-016-1309-9

Liang, 2020, Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones, Int. J. Geogr. Inf. Sci., 34, 1930, 10.1080/13658816.2020.1741591

Brovkin, 2013, Effect of anthropogenic land-use and land cover changes on climate and land carbon storage in CMIP5 projections for the 21st century, J. Clim., 26, 6859, 10.1175/JCLI-D-12-00623.1

Yang, 2020, How can urban blue-green space be planned for climate adaption in high-latitude cities? A seasonal perspective, Sustain. Cities Soc., 53, 101932, 10.1016/j.scs.2019.101932

Polasky, 2010, The Impact of Land-Use Change on Ecosystem Services, Biodiversity and Returns to Landowners: A Case Study in the State of Minnesota, Environ. Res. Econ., 48, 219, 10.1007/s10640-010-9407-0

Lin, Z., Ye, X., Wei, Q., Xin, F., Lu, Z., Kudva, S., and Dai, Q. (2017). Ecosystem services value assessment and uneven development of the Qingjiang River Basin in China. Sustainability, 9.

Zhang, 2018, On the spatial relationship between ecosystem services and urbanization: A case study in Wuhan, China, Sci. Total Environ., 637, 780, 10.1016/j.scitotenv.2018.04.396

Liu, L., Chen, X., Chen, W., and Ye, X. (2020). Identifying the impact of landscape pattern on wcosystem aervices in the middle reaches of the Yangtze River urban agglomerations, China. Int. J. Environ. Res. Public Health, 17.

Li, 2018, Trade-offs and synergies in ecosystem services for the Yinchuan Basin in China, Ecol. Indic., 84, 837, 10.1016/j.ecolind.2017.10.001

Bai, 2020, Scale effects on the relationships between land characteristics and ecosystem services- a case study in Taihu Lake Basin, China, ScTEn, 716, 137081

Wang, 2015, Quantifying changes in multiple ecosystem services during 1992–2012 in the Sanjiang Plain of China, ScTEn, 514, 119

Andrade, 2020, Ecohydrology in a Brazilian tropical dry forest: Thinned vegetation impact on hydrological functions and ecosystem services, J. Hydrol. Reg. Stud., 27, 100649, 10.1016/j.ejrh.2019.100649

Hu, 2020, Assessment of the impact of the Poplar Ecological Retreat Project on water conservation in the Dongting Lake wetland region using the InVEST model, Sci. Total. Environ., 733, 139423, 10.1016/j.scitotenv.2020.139423

Zhu, 2020, Assessment of territorial ecosystem carbon storage based on land use change scenario: A case study in Qihe River Basin, Acta Geogr. Sin., 30, 1507

2015, Modelling regulating ecosystem services trade-offs across landscape scenarios in Trebonsko Wetlands Biosphere Reserve, Czech Republic, Ecol. Model., 295, 207, 10.1016/j.ecolmodel.2014.10.003

Bai, 2013, Modeling hydrological ecosystem services and tradeoffs: A case study in Baiyangdian watershed, China, Environ. Earth Sci., 70, 709, 10.1007/s12665-012-2154-5

Zheng, 2016, Using ecosystem service trade-offs to inform water conservation policies and management practices, Front. Ecol. Environ., 14, 527, 10.1002/fee.1432

Cai, Y., Li, H., Ye, X., and Zhang, H. (2016). Analyzing three-decadal patterns of land use/land cover change and regional ecosystem services at the landscape level: Case study of two coastal metropolitan regions, Eastern China. Sustainability, 8.

Biggs, 2005, Measuring conditions and trends in ecosystem services at multiple scales: The Southern African Millennium Ecosystem Assessment (SA f MA) experience, Philos. Trans. R. Soc. B Biol. Sci., 360, 425, 10.1098/rstb.2004.1594

Lauf, 2014, Linkages between ecosystem services provisioning, urban growth and shrinkage—A modeling approach assessing ecosystem service trade-offs, Ecol. Indic., 42, 73, 10.1016/j.ecolind.2014.01.028

Fu, 2015, Ecosystem Services Evaluation and Its Spatial Characteristics in Central Asia’s Arid Regions: A Case Study in Altay Prefecture, China, Sustainability, 7, 8335, 10.3390/su7078335

Zhao, 2019, Assessing the effects of ecological engineering on carbon storage by linking the CA-Markov and InVEST models, Ecol. Indic., 98, 29, 10.1016/j.ecolind.2018.10.052

Huang, 2020, Ecological response to urban development in a changing socio-economic and climate context: Policy implications for balancing regional development and habitat conservation, Land Use Policy, 97, 104772, 10.1016/j.landusepol.2020.104772

Sohl, 2013, Clarity versus complexity: Land-use modeling as a practical tool for decision-makers, Environ. Manag., 129, 235

Meentemeyer, 2013, FUTURES: Multilevel simulations of emerging urban–rural landscape structure using a stochastic patch-growing algorithm, Ann. Assoc. Am. Geogr., 103, 785, 10.1080/00045608.2012.707591

Yang, 2020, Patch-based cellular automata model of urban growth simulation: Integrating feedback between quantitative composition and spatial configuration, Comput. Environ. Urban Syst., 79, 101402, 10.1016/j.compenvurbsys.2019.101402

Liang, 2021, 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., 85, 101569, 10.1016/j.compenvurbsys.2020.101569

Fang, 2020, Quantifying variations in ecosystem services in altitude-associated vegetation types in a tropical region of China, Sci. Total. Environ., 726, 138565, 10.1016/j.scitotenv.2020.138565

Wu, 2013, Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China, Cities, 31, 276, 10.1016/j.cities.2012.08.003

Yang, 2010, Soil Organic Carbon Distribution of Different Vegetation Typesin the Ili River Valley, Acta Geogr. Sin., 65, 605

Liu, 2002, The land use and land cover change database and its relative studies in China, J. Geogr. Sci., 12, 27

Zheng, 2015, Simulating land use change in urban renewal areas: A case study in Hong Kong, Habitat Int., 46, 23, 10.1016/j.habitatint.2014.10.008

Bocco, 2001, Predicting land-cover and land-use change in the urban fringe: A case in Morelia city, Mexico, Land. Urban Plan., 55, 271, 10.1016/S0169-2046(01)00160-8

Yao, 2017, Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata, Int. J. Geogr. Inf. Sci., 31, 2452, 10.1080/13658816.2017.1360494

Liu, 2019, Learning from data: A post classification method for annual land cover analysis in urban areas, Isprs J. Photogramm. Rem. Sens., 154, 202, 10.1016/j.isprsjprs.2019.06.006

Ma, 2012, Dunhuang city land use/cover scenario simulation based on Markov and CLUE-S models, Chin. J. Ecol., 31, 1823

Niu, 2019, Ecological engineering projects increased vegetation cover, production, and biomass in semiarid and subhumid Northern China, Land Degrad. Dev., 30, 1620, 10.1002/ldr.3351

Hu, 2013, Simulation of land-use scenarios for Beijing using CLUE-S and Markov composite models, Chin. Geogr. Sci., 23, 92, 10.1007/s11769-013-0594-9

Wong, 2015, Linking ecosystem characteristics to final ecosystem services for public policy, Ecol. Lett., 18, 108, 10.1111/ele.12389

2018, Revision of the Common International Classification for Ecosystem Services (CICES V5.1): A Policy Brief, One Ecosyst., 3, e27108, 10.3897/oneeco.3.e27108

Ahmed, 2002, Millennium ecosystem assessment, Environ. Sci. Pollut. Res., 9, 219, 10.1007/BF02987493

Sun, 2018, Analyzing spatio-temporal changes and trade-offs to support the supply of multiple ecosystem services in Beijing, China, Ecol. Indic., 94, 117, 10.1016/j.ecolind.2018.06.049

Bai, 2018, Developing China’s Ecological Redline Policy using ecosystem services assessments for land use planning, Nat. Commun., 9, 1, 10.1038/s41467-018-05306-1

Marco, 2017, Future ecosystem services from European mountain forests under climate change, J. Appl. Ecol., 54, 389, 10.1111/1365-2664.12772

Samie, A., Deng, X., Jia, S., and Chen, D. (2017). Scenario-Based Simulation on Dynamics of Land-Use-Land-Cover Change in Punjab Province, Pakistan. Sustainability, 9.

Pontius, 2000, Quantification Error versus Location Error in Comparison of Categorical Maps, Photogramm. Eng. Remote Sens., 66, 1011

Gao, 2018, Two Kinds of Ecological Service Values of Soil and Water Conservation in the Ili River Valley, Arid Zone Res., 35, 540

Sun, 2020, Global Spatio—Temporal Assessment of Changes in Multiple Ecosystem Services Under Four IPCC SRES Land—use Scenarios, Earth’s Future, 8, 8, 10.1029/2020EF001668

Liu, 2017, Understanding Land System Change Through Scenario-Based Simulations: A Case Study from the Drylands in Northern China, Environ. Manag., 59, 1, 10.1007/s00267-016-0802-3

Wan, 2015, Effects of urbanization on ecosystem service values in a mineral resource-based city, Habitat Int., 46, 54, 10.1016/j.habitatint.2014.10.020

Hinz, 2020, Agricultural Development and Land Use Change in India: A Scenario Analysis of Trade—Offs Between UN Sustainable Development Goals (SDGs), Earth’s Future, 8, e2019EF001287, 10.1029/2019EF001287

Qi, 2014, Land fragmentation and variation of ecosystem services in the context of rapid urbanization: The case of Taizhou city, China, Stoch. Envrion. Res. Risk Assess., 28, 843, 10.1007/s00477-013-0721-2

Yu, 2020, Critical review on the cooling effect of urban blue-green space: A threshold-size perspective, Urban For. Urban Green., 49, 126630, 10.1016/j.ufug.2020.126630

Lili, 2015, Community Structure of Periphyton and Biological Assessment of Water Quality in the Yili River, Xinjiang Uyghur Autonomous Region, J. Hydroecol., 36, 29

Lu, 2014, Trade-off analyses of multiple ecosystem services by plantations along a precipitation gradient across Loess Plateau landscapes, Landsc. Ecol., 29, 1697, 10.1007/s10980-014-0101-4

Farley, 2004, Soil organic carbon and water retention after conversion of grasslands to pine plantations in the Ecuadorian Andes, Ecosystems, 7, 729, 10.1007/s10021-004-0047-5

Davidson, 2007, Recuperation of nitrogen cycling in Amazonian forests following agricultural abandonment, Nature, 447, 995, 10.1038/nature05900

Farley, 2005, Effects of afforestation on water yield: A global synthesis with implications for policy, Glob. Chang. Biol., 11, 1565, 10.1111/j.1365-2486.2005.01011.x

Geertsema, 2016, Actionable knowledge for ecological intensification of agriculture, Front. Ecol. Environ., 14, 209, 10.1002/fee.1258

Liang, 2018, Urban growth simulation by incorporating planning policies into a CA-based future land-use simulation model, Int. J. Geogr. Inf. Sci., 32, 2294, 10.1080/13658816.2018.1502441