Multi-Scenario Simulation and Assessment of Ecosystem Service Value at the City Level from the Perspective of “Production–Living–Ecological” Spaces: A Case Study of Haikou, China

Abstract

Structural changes in land use caused by urban development are one of the most important threats to ecosystem services. An in-depth study of the impacts that different land use patterns have on ecosystem service value (ESV) can provide guidance for sustainable urban planning and ecological conservation. In this research, we sought to explore the response mechanisms of ecosystem services under different urban development scenarios from the perspective of “production–living–ecological” space (PLES). This study combined the Patch-generating Land Use Simulation (PLUS) model and ESV equivalent factor method to simulate the PLES and ESV of Haikou in 2035 under three scenarios of business as usual (BAU), ecological conservation (EC) and economic development (ED), and used the spatial superposition method, transfer matrix, and optimized cross-sensitivity analysis to explore the influence of the PLES on ecosystem services. The ESV of Haikou showed a declining trend from 2010 to 2020 under the influence of PLES changes and was at risk of further decline in the future. The reduction in the value of the water supply service constituted a major part of the loss of ESV. The simulation results demonstrated that the EC scenario had the most rational and ecologically efficient allocation of PLES, with the highest ESV and the lowest sensitivity to PLES changes. The results of this research can serve as an important reference for optimizing the urban land use structure and maintaining the stability of ecosystem services.

Spatiotemporal Variations of Production–Living–Ecological Space under Various, Changing Climate and Land Use Scenarios in the Upper Reaches of Hanjiang River Basin, China

“…As for the actual situation of the diversity functions of different lands and the previous research results, the production, living and ecological function of different lands were quantitatively evaluated by four grades based on the scoring system [19,35]. Among them, the number 5 refers to the high function index (production function, ecological function or living function) of a land type, 3 means the medium land function, 1 is for the weak function, and 0 indicates that the function of a land type is missing (Table 2) [16,21,35]. The results showed that dryland, paddy field, forest land and grassland in the URHR are the main land use categories, among which forest land occupies the largest proportion (78.87%) (Figure 3).…”

“…In recent years, great efforts have been made in research on PLES: First, in terms of classification and identification of PLES, most researchers divide different lands into three types of ES, LS, and PS on the basis of the predominant function of the land categories and have made numerous investigations about the spatiotemporal patterns of PLES at the national scale [13], provincial scale [14], city and county scale [15,16], township scale [17], economic belt and urban agglomeration [18][19][20], watershed and basin scale [21]. Simultaneously, temporal and spatial changes are inevitably accompanied by the process of the mutual encroachment or tradeoff of PLES, such as the spatial coordination and conflict of PLES [22,23].…”

Spatiotemporal evolution and Sustainably comprehensive zoning optimization of production–living–ecological functions in the Mountain–Flatland areas

“…Based on different scales [ 17 ], various methods have been employed to analyze the spatial and temporal change characteristics of the PLEF, guiding land use, sustainable development, resource optimization, ecological environmental protection and sustainable urban assessment, these methods include land use dynamic attitude [ 18 ], transfer matrix [ 19 ], geological information mapping [ 20 ], standard deviation ellipse [ 21 ], center of gravity offset [ 22 ], spatial correlation [ 23 ], landscape pattern index [ 4 ], bivariate local Moran's I model, as well as the coupled coordination degree model, etc. The study covers various scales, ranging from national [ 6 ] and watershed levels [ 24 ] to provincial [ 25 ], urban cluster [ 26 ], metropolitan area [ 27 ], city [ 28 ], county [ 29 ], township [ 30 ], and administrative village levels [ 31 ].…”

Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin

“…However, the substantial economic and environmental costs are inconsistent with the current concept of comprehensive and coordinated sustainable development. With the economic and social transformation of China [45], the level of urbanization and the income of residents have increased, while the direct food consumption of Chinese residents demonstrated a declining trend. The proportion of grain used as raw feed materials is also increasing.…”