Spatiotemporal evolution and driving factors of ecosystem services based on InVEST-OPGD model: a case study in Kunming
Rapid urbanization exerts great pressure on the regional ecological environment and affects the development of the urban ecosystem. Taking Kunming, a key city in southwest China, as the study area, combined with the the changes of land use and vegetation cover from 2000 to 2020, used the InVEST mode...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Environmental Research Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2515-7620/ade59d |
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| Summary: | Rapid urbanization exerts great pressure on the regional ecological environment and affects the development of the urban ecosystem. Taking Kunming, a key city in southwest China, as the study area, combined with the the changes of land use and vegetation cover from 2000 to 2020, used the InVEST model and spatial autocorrelation analysis method to analyze the spatial and temporal evolution of four ecosystem services (ESs) of water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ) from 2000 to 2020, and the Optimal Parameters-based Geographical Detector (OPGD) model was used to explore its driving factors. The results show that: (1) Forest land was the main type of land use in Kunming, the construction land area increased significantly, the grassland area decreased significantly, and the vegetation coverage showed an overall increasing trend. (2) WY and SC services showed a ‘down-up-down’ trend, decreasing from 2000 to 2010, rising post-2010, and declining again after 2015. CS and HQ services showed a downward trend. Spatially, WY service was ‘low in the northwest and high in the southeast,’ while SC, CS, and HQ services were ‘high in the north and low in the south.’ (3) The four ESs in Kunming demonstrated significant global positive spatial correlations, with local clustering patterns exhibiting spatial heterogeneity. (4) WY, CS, and HQ services were mainly affected by vegetation factor NDVI, and SC was mainly affected by the geographic factor slope. The interaction between driving factors was stronger than that of individual factors, particularly when NDVI interacted with other drivers, resulting in significantly amplified impacts on ESs. This study applied the InVEST-OPGD model to urban ESs research, enhancing the understanding of variations in ESs and their drivers, and offering valuable references for ecosystem management and sustainable development in similar mountain cities. |
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| ISSN: | 2515-7620 |