Spatial Assessment of Ecosystem Services in Zhoushan Archipelago Based on InVEST Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection and Processing
2.3. Methods
2.3.1. Ecosystem Service Function Assessment Methods
2.3.2. Water Conservation
2.3.3. Carbon Storage
2.3.4. Habitat Quality
2.3.5. Soil Conservation
2.3.6. Kruskal–Wallis Test
2.3.7. Principal Component Analysis
3. Results and Analyses
3.1. Evaluation of the Importance of Each Ecosystem Service Function in Zhoushan Archipelago
3.2. Statistics on Ecosystem Services in Zhoushan Archipelago
3.2.1. Kruskal–Wallis Test for Land Use Types and Ecosystem Service Functions
3.2.2. The Primary Contributors to Four Ecosystem Services
3.3. Integrated Ecosystem Service Assessment
4. Discussion and Conclusions
4.1. Discussion
4.2. Conclusions
- (1)
- The spatial distribution of the importance of the four ecosystem services in the Zhoushan Archipelago exhibits a clear pattern. Highly important areas and extremely important areas for water conservation, carbon storage, habitat quality, and soil conservation are concentrated in the central areas of Zhoushan Island, Changtu Island, Qushan Island, Dengbu Island, and Taohua Island. Slightly important areas and lightly important areas for four services are concentrated in the offshore areas of Zhoushan Island, Yushan Island, and Yangshan Island.
- (2)
- Trees, built areas, rangeland, and cropland are significant contributors to the four ecosystem service functions, with trees playing the most substantial role across all functions.
- (3)
- The integrated function of the ecosystem service function of the Zhoushan Archipelago is generally favorable, but highly important and extremely important areas show a decreasing trend from 2017 to 2023, with highly important areas and extremely important areas accounting for 17.29% and 2.33% of the total area, respectively, in 2023. The ecological pattern is mainly concentrated in islands with higher terrain and rich forest resources, such as Taohua Island, Changtu Island, Qushan Island, and Zhujiajian Island.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Assessment, M.E. Ecosystems and Human Well-Being: Biodiversity Synthesis; World Resources Institute: Washington, DC, USA, 2005; Volume 86. [Google Scholar]
- Shoyama, K.; Kamiyama, C.; Morimoto, J.; Ooba, M.; Okuro, T. A review of modeling approaches for ecosystem services assessment in the Asian region. Ecosyst. Serv. 2017, 26, 316–328. [Google Scholar] [CrossRef]
- Liu, Y.; Wu, H.; Xue, J. The invasion and its impact for the spread of Chthamalus challengeri in Zhoushan sea area. J. Fish. China 2014, 38, 1047–1055. [Google Scholar]
- Wang, D.; Yu, M.; Mo, W.; Lv, D.A.; Cheng, J.; Sun, L. Ecological Safety Evaluation for Water Resources of China Based on Pressure-State-Response Model: A Case from Zhoushan Archipelago. Nat. Environ. Pollut. Technol. 2021, 20, 601–612. [Google Scholar] [CrossRef]
- Zhang, H.; Xiao, Y. Planning island sustainable development policy based on the theory of ecosystem services: A case study of Zhoushan Archipelago, East China. Isl. Stud. J. 2020, 15, 237–252. [Google Scholar] [CrossRef]
- Tang, R.; Cai, L.; Yan, X.; Ye, X.; Xu, Y.; Yin, J. Study of the Response of Environmental Factors of the Coastal Area in Zhoushan Fishery to Typhoon In-fa Based on Remote Sensing. Remote Sens. 2023, 15, 3349. [Google Scholar] [CrossRef]
- Gianuca, K.; Silva, T.; Asmus, M. Ecosystem-based spatial modeling: Assessing the supply of hydrological services in a watershed in Southern Brazil. Ecol. Model. 2024, 492, 110723. [Google Scholar] [CrossRef]
- Pashanejad, E.; Thierry, H.; Robinson, B.E.; Parrott, L. The application of semantic modelling to map pollination service provisioning at large landscape scales. Ecol. Model. 2023, 484, 110452. [Google Scholar] [CrossRef]
- Wu, J.; Yang, X. Assessment of Ecological Carrying Capacity in Xilingol League Based on Three-Dimensional Ecological Footprint Model. Sustainability 2025, 17, 128. [Google Scholar] [CrossRef]
- Liu, M.; Tu, Z.; Xu, X.; Wang, Z.; Wang, Y. A data-driven approach for constructing multilayer network-based service ecosystem models. Softw. Syst. Model. 2023, 22, 919–939. [Google Scholar] [CrossRef]
- Sherrouse, B.C.; Semmens, D.J.; Ancona, Z.H. Social Values for Ecosystem Services (SolVES): Open-source spatial modeling of cultural services. Environ. Model. Softw. 2022, 148, 105259. [Google Scholar] [CrossRef]
- Chen, X.; Yu, L.; Du, Z.; Xu, Y.; Zhao, J.; Zhao, H.; Zhang, G.; Peng, D.; Gong, P. Distribution of ecological restoration projects associated with land use and land cover change in China and their ecological impacts. Sci. Total Environ. 2022, 825, 153938. [Google Scholar] [CrossRef] [PubMed]
- Yang, Q.; Zhang, P.; Qiu, X.; Xu, G.; Chi, J. Spatial-temporal variations and trade-offs of ecosystem services in Anhui Province, China. Int. J. Environ. Res. Public Health 2023, 20, 855. [Google Scholar] [CrossRef] [PubMed]
- Fan, L.; Wang, X.; Chen, Z.; Chen, R.; Liu, X.; He, Y.; Wang, S. Analysis of Spatial and Temporal Evolution of Ecosystem Services and Driving Factors in the Yellow River Basin of Henan Province, China. Forests 2024, 15, 1547. [Google Scholar] [CrossRef]
- Miao, P.; Li, C.; Xia, B.; Zhao, X.; Wu, Y.; Zhang, C.; Wu, J.; Cheng, F.; Pu, J.; Huang, P.; et al. Incorporating Ecosystem Service Trade-Offs and Synergies with Ecological Sensitivity to Delineate Ecological Functional Zones: A Case Study in the Sichuan-Yunnan Ecological Buffer Area, China. Land 2024, 13, 1503. [Google Scholar] [CrossRef]
- Lei, J.; Zhang, L.; Wu, T.; Chen, X.; Li, Y.; Chen, Z. Spatial-temporal evolution and driving factors of water yield in three major drainage basins of Hainan Island based on land use change. Front. For. Glob. Chang. 2023, 6, 1131264. [Google Scholar] [CrossRef]
- Yao, X.; Zhou, L.; Wu, T.; Yang, X.; Ren, M. Ecosystem services in National Park of Hainan Tropical Rainforest of China: Spatiotemporal dynamics and conservation implications. J. Nat. Conserv. 2024, 80, 126649. [Google Scholar] [CrossRef]
- Lai, J.; Qi, S.; Chen, J.; Guo, J.; Wu, H.; Chen, Y. Exploring the spatiotemporal variation of carbon storage on Hainan Island and its driving factors: Insights from InVEST, FLUS models, and machine learning. Ecol. Indic. 2025, 172, 113236. [Google Scholar] [CrossRef]
- Wu, Q.; Wang, L.; Wang, T.; Ruan, Z.; Du, P. Spatial–temporal evolution analysis of multi-scenario land use and carbon storage based on PLUS-InVEST model: A case study in Dalian, China. Ecol. Indic. 2024, 166, 112448. [Google Scholar] [CrossRef]
- Qiu, S.; Yue, W.; Zhang, H.; Qi, J. Island ecosystem services value, land-use change, and the National New Area Policy in Zhoushan Archipelago, China. Isl. Stud. J. 2017, 12, 177–198. [Google Scholar] [CrossRef]
- Shao, X.; Jing, C.; Qi, J.; Jiang, J.; Liu, Q.; Cai, X. Impacts of land use and planning on island ecosystem service values: A case study of Dinghai District on Zhoushan Archipelago, China. Ecol. Process. 2017, 6, 27. [Google Scholar] [CrossRef]
- Xiao, Y.; Zhang, H.; Ma, K.; Perera, H.A.C.C.; Ramli, M.Z.; Deng, Y. Exploring the Relationships between Tradeoffs and Synergies among Island Ecosystem Service Bundles: A Study on Zhoushan Archipelago Located on the Southeast Coast of China. Sustainability 2024, 16, 394. [Google Scholar] [CrossRef]
- Cao, W.; Zhou, Y.; Li, R.; Li, X.; Zhang, H. Monitoring long-term annual urban expansion (1986–2017) in the largest archipelago of China. Sci. Total Environ. 2021, 776, 146015. [Google Scholar] [CrossRef]
- Zhou, B.; Xu, J.M.; Yu, H.; Wang, L.T. Comprehensive assessment of ecological risks of Island destinations—A case of Mount Putuo Island, China. Ecol. Indic. 2023, 154, 110783. [Google Scholar] [CrossRef]
- Li, W.; Geng, J.; Bao, J.; Lin, W.; Wu, Z.; Fan, S. Analysis of spatial and temporal variations in ecosystem service functions and drivers in Anxi county based on the InVEST model. Sustainability 2023, 15, 10153. [Google Scholar] [CrossRef]
- He, F.; Jin, J.; Zhang, H.; Yuan, L. The change of ecological service value and the promotion mode of ecological function in mountain development using InVEST model. Arab. J. Geosci. 2021, 14, 510. [Google Scholar] [CrossRef]
- Zhang, L.; Hickel, K.; Dawes, W.R.; Chiew, F.H.; Western, A.W.; Briggs, P.R. A rational function approach for estimating mean annual evapotranspiration. Water Resour. Res. 2004, 40, 89–97. [Google Scholar] [CrossRef]
- Donohue, R.J.; Roderick, M.L.; McVicar, T.R. Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko’s hydrological model. J. Hydrol. 2012, 436, 35–50. [Google Scholar] [CrossRef]
- Li, M.; Liang, D.; Xia, J.; Song, J.; Cheng, D.; Wu, J.; Cao, Y.; Sun, H.; Li, Q. Evaluation of water conservation function of Danjiang River Basin in Qinling Mountains, China based on InVEST model. J. Environ. Manag. 2021, 286, 112212. [Google Scholar] [CrossRef]
- Zhang, B.; Li, W.; Xie, G.; Xiao, Y. Water conservation of forest ecosystem in Beijing and its value. Ecol. Econ. 2010, 69, 1416–1426. [Google Scholar]
- Wang, Y.; Ye, A.; Peng, D.; Miao, C.; Di, Z.; Gong, W. Spatiotemporal variations in water conservation function of the Tibetan Plateau under climate change based on InVEST model. J. Hydrol. Reg. Stud. 2022, 41, 101064. [Google Scholar] [CrossRef]
- Geng, J.; Yuan, M.; Xu, S.; Bai, T.; Xiao, Y.; Li, X.; Xu, D. Urban expansion was the main driving force for the decline in ecosystem services in hainan island during 1980–2015. Int. J. Environ. Res. Public Health 2022, 19, 15665. [Google Scholar] [CrossRef] [PubMed]
- Yin, L.; Zheng, W.; Shi, H.; Ding, D. Ecosystem services assessment and sensitivity analysis based on ANN model and spatial data: A case study in Miaodao Archipelago. Ecol. Indic. 2022, 135, 108511. [Google Scholar] [CrossRef]
- Quan, W.; Huang, X.; Xu, G.; Hao, J.; Lv, K.; Jiang, X. Study on the influence mechanism of land use on carbon storage under multiple scenarios: A case study of Wenzhou. Open Geosci. 2024, 16, 20220735. [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]
- Cao, W.; Li, R.; Chi, X.; Chen, N.; Chen, J.; Zhang, H.; Zhang, F. Island urbanization and its ecological consequences: A case study in the Zhoushan Island, East China. Ecol. Indic. 2017, 76, 1–14. [Google Scholar] [CrossRef]
- Jia, X.; Zhu, J.; Li, Y.; Wu, W.; Hu, X. Analysis of the driving role and impact of road construction on carbon stock. Environ. Sci. Pollut. Res. 2023, 30, 67131–67149. [Google Scholar] [CrossRef]
- Wen, J.; Fu, W. Spatial and Temporal Variability of Ecosystem Support Services and Drivers in Metropolitan Areas Based on the Invest Model. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2022, 10, 29–35. [Google Scholar] [CrossRef]
- Wang, B.; Cheng, W. Effects of land use/cover on regional habitat quality under different geomorphic types based on InVEST model. Remote Sens. 2022, 14, 1279. [Google Scholar] [CrossRef]
- Luo, X.; Luo, Y.; Le, F.; Zhang, Y.; Zhang, H.; Zhai, J. Spatiotemporal Variation and Prediction Analysis of Land Use/Land Cover and Ecosystem Service Changes in Gannan, China. Sustainability 2024, 16, 1551. [Google Scholar] [CrossRef]
- Kim, T.; Song, C.; Lee, W.-K.; Kim, M.; Lim, C.H.; Jeon, S.W.; Kim, J. Habitat quality valuation using InVEST model in Jeju Island. J. Korean Soc. Environ. Restor. Technol. 2015, 18, 1–11. [Google Scholar] [CrossRef]
- Chen, Y.; Zhang, F.; Lin, J. Projecting Future Land Use Evolution and Its Effect on Spatiotemporal Patterns of Habitat Quality in China. Appl. Sci. 2025, 15, 1042. [Google Scholar] [CrossRef]
- Moreira, M.; Fonseca, C.; Vergílio, M.; Calado, H.; Gil, A. Spatial assessment of habitat conservation status in a Macaronesian island based on the InVEST model: A case study of Pico Island (Azores, Portugal). Land Use Policy 2018, 78, 637–649. [Google Scholar] [CrossRef]
- Wei, Q.; Abudureheman, M.; Halike, A.; Yao, K.; Yao, L.; Tang, H.; Tuheti, B. Temporal and spatial variation analysis of habitat quality on the PLUS-InVEST model for Ebinur Lake Basin, China. Ecol. Indic. 2022, 145, 109632. [Google Scholar] [CrossRef]
- He, N.; Guo, W.; Wang, H.; Yu, L.; Cheng, S.; Huang, L.; Jiao, X.; Chen, W.; Zhou, H. Temporal and spatial variations in landscape habitat quality under multiple land-use/land-cover scenarios based on the PLUS-InVEST model in the Yangtze River Basin, China. Land 2023, 12, 1338. [Google Scholar] [CrossRef]
- Ai, B.; Tian, Y.; Wang, P.; Gan, Y.; Luo, F.; Shi, Q. Vulnerability analysis of coastal zone based on InVEST model in Jiaozhou Bay, China. Sustainability 2022, 14, 6913. [Google Scholar] [CrossRef]
- Jian, Z.; Sun, Y.; Wang, F.; Zhou, C.; Pan, F.; Meng, W.; Sui, M. Soil conservation ecosystem service supply-demand and multi scenario simulation in the Loess Plateau, China. Glob. Ecol. Conserv. 2024, 49, e02796. [Google Scholar] [CrossRef]
- Wang, X.; Liu, X.; Wu, Y.; Chen, R.; Wang, S. Dynamic assessment and change analysis of ecosystem service value based on physical assessment method in Cili County, China. Forests 2023, 14, 869. [Google Scholar] [CrossRef]
- Wenger, A.S.; Atkinson, S.; Santini, T.; Falinski, K.; Hutley, N.; Albert, S.; Horning, N.; Watson, J.E.M.; Mumby, P.J.; Jupiter, S.D. Predicting the impact of logging activities on soil erosion and water quality in steep, forested tropical islands. Environ. Res. Lett. 2018, 13, 044035. [Google Scholar] [CrossRef]
- Du, R.; Liu, B.; Chen, Z.; Xu, M. Exploring the multiscale island terrestrial ecosystem service relationships and coastal vulnerability under the influence of coastal ecosystems. Ocean. Coast. Manag. 2024, 256, 107267. [Google Scholar] [CrossRef]
- Inácio, M.; Baltranaitė, E.; Bogdzevič, K.; Kalinauskas, M.; Pinto, L.V.; Barceló, D.; Pereira, P. Mapping and assessing the future provision of lake ecosystem services in Lithuania. J. Environ. Manag. 2024, 372, 123349. [Google Scholar] [CrossRef]
- Fentaw, G.; Beneberu, G.; Wondie, A.; Eneyew, B.G. Ecosystem services of wetlands in the upper Abbay River basin, Ethiopia. Ecol. Indic. 2025, 171, 113142. [Google Scholar] [CrossRef]
- Jolliffe, I.T.; Cadima, J. Principal component analysis: A review and recent developments. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2016, 374, 20150202. [Google Scholar] [CrossRef] [PubMed]
- Bai, Y.; Zhuang, C.; Ouyang, Z.; Zheng, H.; Jiang, B. Spatial characteristics between biodiversity and ecosystem services in a human-dominated watershed. Ecol. Complex. 2011, 8, 177–183. [Google Scholar] [CrossRef]
- Abdi, H.; Williams, L.J. Principal component analysis. Wiley Interdiscip. Rev. Comput. Stat. 2010, 2, 433–459. [Google Scholar] [CrossRef]
- Salata, S.; Grillenzoni, C. A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy. Ecol. Indic. 2021, 127, 107758. [Google Scholar] [CrossRef]
- Depellegrin, D.; Pereira, P.; Misiunė, I.; Egarter-Vigl, L. Mapping ecosystem services potential in Lithuania. Int. J. Sustain. Dev. World Ecol. 2016, 23, 441–555. [Google Scholar] [CrossRef]
- Zou, T.; Yoshino, K. Environmental vulnerability evaluation using a spatial principal components approach in the Daxing’anling region, China. Ecol. Indic. 2017, 78, 405–415. [Google Scholar] [CrossRef]
- Seto, K.C.; Sánchez-Rodríguez, R.; Fragkias, M. The new geography of contemporary urbanization and the environment. Annu. Rev. Environ. Resour. 2010, 35, 167–194. [Google Scholar] [CrossRef]
- He, C.; Zhang, D.; Huang, Q.; Zhao, Y. Assessing the potential impacts of urban expansion on regional carbon storage by linking the LUSD-urban and InVEST models. Environ. Model. Softw. 2016, 75, 44–58. [Google Scholar] [CrossRef]
- Hong, H.-J.; Kim, C.-K.; Lee, H.-W.; Lee, W.-K. Conservation, restoration, and sustainable use of biodiversity based on habitat quality monitoring: A case study on Jeju Island, South Korea (1989–2019). Land 2021, 10, 774. [Google Scholar] [CrossRef]
- De Groot, R.S.; Wilson, M.A.; Boumans, R.M. A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol. Econ. 2002, 41, 393–408. [Google Scholar] [CrossRef]
- Li, J.; Liu, Y.; Gani, A.A.; Wu, J.; Dai, Y. Identification of ecological security patterns for the Qiandongnan Ecotourism Area in Southwest China using InVEST and circuit theory. Forests 2023, 14, 1316. [Google Scholar] [CrossRef]
- Butsic, V.; Shapero, M.; Moanga, D.; Larson, S. Using InVEST to assess ecosystem services on conserved properties in Sonoma County, CA. Calif. Agric. 2017, 71, 81–89. [Google Scholar] [CrossRef]
- Wang, R.; Zhao, J.; Chen, G.; Lin, Y.; Yang, A.; Cheng, J. Coupling PLUS–InVEST model for ecosystem service research in Yunnan Province, China. Sustainability 2022, 15, 271. [Google Scholar] [CrossRef]
- Zhang, S.; Zhang, Z.; Wang, J.; Zhang, Y.; Wu, J.; Zhang, X. Effects of ecological control line on habitat connectivity: A case study of Shenzhen, China. Ecol. Indic. 2024, 167, 112583. [Google Scholar] [CrossRef]
- Hong, W.; Yang, C.; Chen, L.; Zhang, F.; Shen, S.; Guo, R. Ecological control line: A decade of exploration and an innovative path of ecological land management for megacities in China. J. Environ. Manag. 2017, 191, 116–125. [Google Scholar] [CrossRef]
- Arcidiacono, A.; Ronchi, S.; Salata, S. Ecosystem Services assessment using InVEST as a tool to support decision making process: Critical issues and opportunities. In Proceedings of the International Conference on Computational Science and Its Applications, Banff, AB, Canada, 22–25 June 2015; Springer International Publishing: Cham, Switzerland, 2015; Volume 9158, pp. 35–49. [Google Scholar]
Data | Data Source and Processing Method |
---|---|
Land use | Land use types for 2017, 2020, and 2023 come from ESRI (https://livingatlas.arcgis.com, accessed on 16 October 2024), with a spatial resolution of 10 m. |
Precipitation | Data on average rainfall were sourced from the National Meteorological Information Centre (http://data.cma.cn, accessed on 22 March 2025), using data from meteorological stations in the Zhoushan Archipelago and Ningbo City. Seven years of precipitation data were obtained from 2017 to 2023, and 2017, 2020, and 2023 were selected as the characteristic years. To minimize the impact of extreme precipitation events, the average precipitation of the one year preceding and following each representative year was used to derive the characteristic values for each station. For spatial analysis, Kriging interpolation was applied using ArcGIS Spatial Analyst tools. The resulting interpolated data were clipped according to the administrative boundaries of the Zhoushan Archipelago to generate raster precipitation datasets for the three selected years. |
Potential evapotranspiration | Data on average annual temperature and rainfall were sourced from the National Meteorological Information Centre (http://data.cma.cn, accessed on 22 March 2025), calculated by the modified Hargreaves equation. After obtaining the results, Kriging interpolation was carried out for each meteorological station to obtain the reference evapotranspiration raster data for the study area. |
Soil data | Soil type data are from the China Soil Database (http://vdb3.soil.csdb.cn/, accessed on 18 September 2024), including soil type, soil texture (%clay, %sand, %silt, %organic carbon), and soil depth, with a spatial resolution of 1000 m. |
Digital elevation model | The Geospatial Data Cloud (https://www.gscloud.cn/, accessed on 18 September 2024) provided the digital elevation model (DEM) data, with a spatial resolution of 30 m. |
Topographic index | Calculations were made based on the DEM and soil depth using the spatial analysis tool in ArcGIS. |
Soil saturated hydraulic conductivity | Calculations were made based on soil texture data using the raster calculator tool in ArcGIS. |
Percentage slope | Calculations were made based on DEM data using the slope tool in ArcGIS. |
Rainfall erosion factor | Calculations were made based on precipitation amounts using the Raster Calculator tool in ArcGIS. |
Soil erosion factor | Calculations were made based on soil texture data using the raster calculator tool in ArcGIS. |
LULC | Kc | Root Depth (mm) |
---|---|---|
Water | 1 | 400 |
Trees | 1 | 3500 |
Flooded Vegetation | 0.8 | 3500 |
Crops | 0.65 | 300 |
Built Area | 0.3 | 1 |
Bare Ground | 0.2 | 1 |
Rangeland | 0.65 | 1500 |
LULC | ||||
---|---|---|---|---|
Water | 0.685 | 0 | 83.962 | 0 |
Trees | 68.781 | 21.734 | 132.572 | 8.131 |
Flooded Vegetation | 5.74 | 5.47 | 77.65 | 0 |
Crops | 5.961 | 1.274 | 96.635 | 0 |
Built Area | 6.5 | 1.4 | 67.3 | 0 |
Bare Ground | 0.113 | 0 | 75.431 | 0 |
Rangeland | 2.635 | 10.043 | 103.01 | 0.879 |
Factor | Maximum Threat Range (Kilometers) | Weight | Distance Decay |
---|---|---|---|
Crops | 4 | 0.6 | Linear |
Built Area | 8 | 1 | Exponential |
Bare Ground | 2 | 0.4 | Linear |
Factor | Habitat Resilience | Susceptibility | ||
---|---|---|---|---|
Crops | Built Area | Bare Ground | ||
Water | 0.9 | 0.3 | 0.5 | 0.3 |
Trees | 1 | 0.65 | 0.75 | 0.6 |
Flooded Vegetation | 0.9 | 0.55 | 0.7 | 0.55 |
Crops | 0.4 | 0.1 | 0.2 | 0.1 |
Built Area | 0 | 0 | 0 | 0 |
Bare Ground | 0.2 | 0.1 | 0.2 | 0.1 |
Rangeland | 0.8 | 0.5 | 0.6 | 0.4 |
LULC | ||
---|---|---|
Water | 0 | 0.2 |
Trees | 0.12 | 0.7 |
Flooded Vegetation | 0.34 | 0.2 |
Crops | 0.35 | 0.29 |
Built Area | 0.25 | 0.16 |
Bare Ground | 0.4 | 0.2 |
Rangeland | 0.3 | 0.5 |
Ecosystem Service Function | A | B | C | D | E | |||||
---|---|---|---|---|---|---|---|---|---|---|
Area /km2 | Ratio /% | Area /km2 | Ratio /% | Area /km2 | Ratio /% | Area /km2 | Ratio /% | Area /km2 | Ratio /% | |
Water Conservation | 538.05 | 40.01 | 238.94 | 17.77 | 340.59 | 25.33 | 149.63 | 11.13 | 77.59 | 5.77 |
Carbon Storage | 441.07 | 32.80 | 234.31 | 17.42 | 299.34 | 22.26 | 243.85 | 18.13 | 126.23 | 9.39 |
Habitat Quality | 524.43 | 38.43 | 238.84 | 17.50 | 226.99 | 16.63 | 198.25 | 14.53 | 176.29 | 12.92 |
Soil Conservation | 744.7 | 54.69 | 244.9 | 17.99 | 198.12 | 14.55 | 132.12 | 9.70 | 41.79 | 3.07 |
Ecosystem Service Function | Land Use | N | M (P25, P75) | Z | p |
---|---|---|---|---|---|
Water Conservation | Water | 191 | 0 (0, 0) | 1544.516 | <0.01 |
Trees | 742 | 64.07 (59.04, 70.72) | |||
Flooded Vegetation | 13 | 71.93 (57.95, 87.12) | |||
Crops | 92 | 93.83 (92.31, 96.18) | |||
Built Area | 778 | 0 (0, 0) | |||
Bare Ground | 31 | 0 (0, 0) | |||
Rangeland | 112 | 112.73 (98.79, 116.05) | |||
Carbon Storage | Water | 191 | 0.85 (0.75, 0.85) | 1958.000 | <0.01 |
Trees | 742 | 2.31 (2.31, 2.31) | |||
Flooded Vegetation | 13 | 0.76 (0.75, 0.96) | |||
Crops | 92 | 1.04 (0.75, 1.17) | |||
Built Area | 778 | 0.75 (0.75, 0.75) | |||
Bare Ground | 31 | 0.75 (0.75, 0.76) | |||
Rangeland | 112 | 1.17 (0.85, 1.17) | |||
Habitat Quality | Water | 191 | 0.96 (0.93, 0.98) | 1756.408 | <0.01 |
Trees | 742 | 0.79 (0.73, 0.86) | |||
Flooded Vegetation | 13 | 0.91 (0.86, 0.93) | |||
Crops | 92 | 0.3 (0.3, 0.3) | |||
Built Area | 778 | 0.1 (0.1, 0.1) | |||
Bare Ground | 31 | 0.4 (0.4, 0.4) | |||
Rangeland | 112 | 0.78 (0.74, 0.87) | |||
Soil Conservation | Water | 191 | 0.31 (0.05, 1.34) | 634.720 | <0.01 |
Trees | 742 | 4.67 (2.22, 7.37) | |||
Flooded Vegetation | 13 | 0.05 (0.04, 0.42) | |||
Crops | 92 | 0.05 (0.04, 0.8) | |||
Built Area | 778 | 0.75 (0.05, 1.83) | |||
Bare Ground | 31 | 0.05 (0.04, 2.39) | |||
Rangeland | 112 | 1 (0.05, 2.63) |
Test | Statistic | |||
---|---|---|---|---|
2017 | 2020 | 2023 | ||
KMO | 0.842 | 0.855 | 0.841 | |
Bartlett’s test | Approx. Chi-Square | 27,606.11 | 24,252.97 | 24,252.97 |
df | 6 | 6 | 6 | |
Sig. | 0.000 | 0.000 | 0.000 |
Principal Component | Eigenvalues | Percent of Eigenvalues/% | Accumulative of Eigenvalues/% | |
---|---|---|---|---|
2017 | 1 | 3.41 | 85.251 | 85.251 |
2 | 0.372 | 9.31 | 94.561 | |
3 | 0.182 | 4.558 | 99.119 | |
4 | 0.035 | 0.881 | 100 | |
2020 | 1 | 3.497 | 87.423 | 87.423 |
2 | 0.325 | 8.118 | 95.541 | |
3 | 0.113 | 2.826 | 98.367 | |
4 | 0.065 | 1.633 | 100 | |
2023 | 1 | 3.401 | 85.014 | 85.251 |
2 | 0.353 | 8.836 | 94.561 | |
3 | 0.175 | 4.365 | 99.119 | |
4 | 0.071 | 1.786 | 100 |
Ecosystem Service Functions | Water Yield | Soil Conservation | Carbon Storage | Habitat Quality |
---|---|---|---|---|
2017 | 0.25 | 0.23 | 0.26 | 0.26 |
2020 | 0.23 | 0.25 | 0.26 | 0.26 |
2023 | 0.26 | 0.23 | 0.25 | 0.26 |
Ecosystem Service Functions | A | B | C | D | E | |||||
---|---|---|---|---|---|---|---|---|---|---|
Area /km2 | Ratio /% | Area /km2 | Ratio /% | Area /km2 | Ratio /% | Area /km2 | Ratio /% | Area /km2 | Ratio /% | |
2017 | 504.77 | 33.81 | 299.99 | 20.09 | 348.17 | 23.32 | 296.47 | 19.86 | 43.65 | 2.92 |
2020 | 514.56 | 34.44 | 264.49 | 17.70 | 403.64 | 27.02 | 272.92 | 18.27 | 38.44 | 2.57 |
2023 | 538.75 | 36.06 | 244.61 | 16.37 | 417.67 | 27.96 | 258.28 | 17.29 | 34.75 | 2.33 |
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Liu, M.; Zhao, S. Spatial Assessment of Ecosystem Services in Zhoushan Archipelago Based on InVEST Model. Sustainability 2025, 17, 3913. https://doi.org/10.3390/su17093913
Liu M, Zhao S. Spatial Assessment of Ecosystem Services in Zhoushan Archipelago Based on InVEST Model. Sustainability. 2025; 17(9):3913. https://doi.org/10.3390/su17093913
Chicago/Turabian StyleLiu, Meimei, and Sheng Zhao. 2025. "Spatial Assessment of Ecosystem Services in Zhoushan Archipelago Based on InVEST Model" Sustainability 17, no. 9: 3913. https://doi.org/10.3390/su17093913
APA StyleLiu, M., & Zhao, S. (2025). Spatial Assessment of Ecosystem Services in Zhoushan Archipelago Based on InVEST Model. Sustainability, 17(9), 3913. https://doi.org/10.3390/su17093913