Detecting the Complex Relationships and Driving Mechanisms of Key Ecosystem Services in the Central Urban Area Chongqing Municipality, China

Abstract

Ecosystem services (ESs) are highly vulnerable to human activities. Understanding the relationships among multiple ESs and driving mechanisms are crucial for multi-objective management in complex social-ecological systems. The goals of this study are to quantitatively evaluate and identify ESs hotspots, explore the relationships among ESs and elucidate the driving mechanisms. Taking central urban area Chongqing municipality as the study area, biodiversity (BI), carbon fixation (CF), soil conservation (SC) and water conservation (WC) were evaluated based on the InVEST model and ESs hotspots were identified. The complex interactions among multiple ESs were determined by utilizing multiple methods: spearman correlation analysis, bivariate local spatial autocorrelation and K-means clustering. The linear or nonlinear relationships between ESs and drivers were discussed by generalized additive models (GAMs). The results showed that during 2000–2018, except for CF that exhibited no obvious change, all other ESs showed a decrease tendency. High ESs were clustered in mountains, while ESs in urban areas were lowest. At administrative districts scale, ESs were relatively higher in Beibei, Banan and Yubei, and drastically decreased in Jiangbei. Multiple ES hotspots demonstrated clear spatial heterogeneity, which were mainly composed of forestland and distributed in mountainous areas with high altitude and steep slope. The relationships between ES pairs were synergistic at the entire scale. However, at grid scale, the synergies were mainly concentrated in the high-high and low-low clusters, i.e., mountainous areas and urban central areas. Five ESs bundles presented the interactions among multiple ESs, which showed well correspondence with social-ecological conditions. GAMs indicated that forestland and grassland had positive impact on BI and CF. Additionally, SC was mainly determined by geomorphological factors, while WC were mainly influenced by precipitation. Furthermore, policy factors were confirmed to have a certain positive effect on ESs. This study provides credible references for ecosystem management and urban planning.

Quantifying the Relationship between Land Use Intensity and Ecosystem Services’ Value in the Hanjiang River Basin: A Case Study of the Hubei Section

“…Xie et al (2003 and 2008) [ 6 , 7 ] built upon Costanza et al (1997) and proposed an evaluation method suitable for assessing the economic value of terrestrial ES in China based on surveys of over 200 Chinese ecologists [ 8 ]. Much of the literature on ES has focused on the evaluation of ES value (ESV) [ 9 , 10 , 11 ], the driving mechanism of ES variation [ 12 , 13 , 14 ], the integration of ES in landscape planning and decision making [ 15 , 16 ], and analysis of ES synergies and tradeoffs [ 17 , 18 ]. Recent research has begun to investigate the coupling coordinative relationship between ES and socio-economic development, such as sustainable development [ 19 , 20 ], human activities’ intensity [ 21 ], urbanization [ 22 ], etc.…”

Quantifying the Ecosystem Services of Soda Saline-Alkali Grasslands in Western Jilin Province, NE China

“…Given the extent of ecosystem degradation resulting from environmental changes and human activity [1,2], restoration efforts have increasingly focused on biodiversity and ecosystem services [3,4]. Grassland, which is widely distributed around the globe, is an important terrestrial ecosystem due to a wide range of ecosystem services such as climate regulation, wind prevention and sand fixation, water conservation, biodiversity protection, and carbon sequestration [5][6][7][8][9]. Grassland is also an important ecosystem and natural resource in China, covering an area of approximately 4 million km 2 , which accounts for more than 40% of the country's land area and represents a major contributor to net ecosystem productivity [10].…”

“…The increasingly serious salinization will lead to a gradual decrease in the function of grassland, which will seriously threaten the ecological and economic development of the region. Therefore, investigating grassland ecosystem services in the study area, correctly recognizing the relationships between these services, and identifying ecosystem service hotspots [9,32] will be conducive to effectively classifying grassland ecosystem service types and promoting the sustainable development of the grassland ecosystem.…”

“…Cultivated land; 2 Forest land;3 Water land;4 Urban and rural construction land;5 Unused land;6 High-cover grassland; 7 Medium-cover grassland; 8 Low-cover grassland;9 Saline-alkali land.…”