Driving Forces on the Distribution of Urban Ecosystem’s Non-Point Pollution Reduction Service

Author:

Shu Chengji12ORCID,Du Kaiwei3,Han Baolong1,Chen Zhiwen14,Wang Haoqi15,Ouyang Zhiyun1ORCID

Affiliation:

1. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

2. University of Chinese Academy of Sciences, Bejing 100049, China

3. Department of Landscape Architecture and Horticulture, College of Architecture and Design, Chongqing College of Humanities, Science & Technology, Chongqing 401524, China

4. Laboratory of Ecosystem Services and Spatial Planning, College of Landscape Architecture and Art Design, Hunan Agricultural University, Changsha 410128, China

5. Department of Landscape Architecture, College of Horticulture and Gardens, Southwest University, Chongqing 400100, China

Abstract

In the context of increasing urbanization and worsening environmental pollution, nonpoint source pollution during high-frequency rainfall has become a major ecological problem that endangers residents in cities. This study takes Shenzhen as an example. On the basis of a large number of soil sample test data, and combined with relevant environmental variables, it has drawn the high-resolution, high-precision spatial distribution maps of soil attributes within the city. In addition, this paper combines the revised universal soil loss equation and the GeoDetector model to evaluate the supply capacity of nonpoint source reduction services in the city’s ecological space and the main driving factors of spatial distribution characteristics for different types of land. The study found that increasing soil point density and combining environmental variables can help improve the accuracy of spatial mapping for soil attributes. The ME, MSE, ASE, RMSE, and RMSSE of spatial mapping all meet the accuracy evaluation criteria and are better than many existing studies; the spatial distribution characteristics of soil attributes and nonpoint source reduction services show significant differences among the whole city, secondary administrative regions, and different types of land; the GeoDetector results show that among the three main types of land use (forested land, industrial land, and street town residential land), topographic factors, habitat-quality factors, and ecosystem types have the greatest impact on the spatial differentiation characteristics of nonpoint source reduction services. Among climate factors, only precipitation factors have the greatest impact on the spatial differentiation characteristics of services. Facing the above factors, the q-values calculated by the GeoDetector are all higher than 10%. The results of this study can provide information for making better decisions on regional ecological system management and soil protection and on restoration work aimed at improving nonpoint source reduction services.

Funder

Technologies and Models for Optimizing Urban Ecological Spatial Patterns and Enhancing Func-tions with Multi-objective Synergy

National Key Research and Development Program of China

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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