Author
Listed:
- Bowen Zhang
(School of Architecture and Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, China)
- Xianglong Tang
(School of Architecture and Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, China)
- Jiexin Cui
(School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710000, China)
- Leshan Cai
(School of Architecture and Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, China)
Abstract
Megacities in developing countries are still undergoing rapid urbanization, with different cities exhibiting ecosystem services (ESs) heterogeneity. Evaluating ESs among various cities and analyzing the influencing factors from a resilience perspective can effectively enhance the ability of cities to deal with and react quickly to the risks of uncertainty. This approach is also crucial for optimizing ecological security patterns. This study focuses on Xi’an and Jinan, two important megacities along the Yellow River in China. First, we quantified four ecosystem services for both cities: carbon storage (CS), habitat quality (HQ), food production (FP), and soil conservation (SC). Second, we analyzed the synergies and trade-offs between these ESs using bivariate local spatial autocorrelation and Spearman’s rank correlation coefficient. Finally, we conducted a driver analysis using the Geographic Detector. Results: (1) The spatial and temporal distribution of the four ESs in Xi’an and Jinan is quite different, but both cities show lower ES levels in the urban core area. (2) ESs in Xi’an showed a strong synergistic effect. Among them, CS-HQ had the strongest synergy of 0.93. In terms of space, the north is dominated by low–low clustering, while the south is dominated by high–high clustering. The FP-SC in Jinan showed a trade-off effect of −0.35 in 2000, which gradually weakened over time and was mainly distributed in the northern area of the city where cropland and construction were concentrated. (3) Edge density, patch density, and NDVI have the greatest influence on CS in Xi’an and Jinan. DEM, slope, and patch density have the greatest influence on Xi’an HQ. Temperature, edge density, and patch density have the greatest impact on Jinan HQ. NDVI and temperature have the greatest influence on FP in the two cities. DEM, slope, and edge density have the greatest influence on SC. Landscape fragmentation has a great impact on CS, HQ, and SC in Xi’an and Jinan. Due to insufficient research data, this study focused on only four ESs in Xi’an and Jinan, the megacities in the middle and lower reaches of the Yellow River. However, the research results can provide a new perspective for solving the problem of regional sustainable development and new directions and ideas for follow-up research in this field.
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