Evaluation of Social Values for Ecosystem Services in Urban Riverfront Space Based on the SolVES Model: A Case Study of the Fenghe River, Xi'an, China | JoVE Visualize

Evaluation of Social Values for Ecosystem Services in Urban Riverfront Space Based on the SolVES Model: A Case Study of the Fenghe River, Xi'an, China

Zhicheng Zhang¹, Hongjuan Zhang², Juan Feng¹

¹College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.

International Journal of Environmental Research and Public Health|April 3, 2021

View abstract on PubMed

Summary

Urban riverfront ecosystems offer valuable services, but unsustainable land use degrades them. This study used the SolVES model to assess social values and identify key environmental drivers like landscape type and proximity to water and roads.

Area of Science:

Urban ecology
Ecosystem services valuation
Environmental geography

Background:

Urban riverfronts provide diverse ecosystem services.
Unsustainable land-use changes lead to ecological degradation and social value gain at a high ecological cost.
Assessing social values is crucial for sustainable urban development.

Purpose of the Study:

To evaluate the social value of ecosystem services on the Fenghe River's east bank.
To investigate the influence of environmental variables on social value distribution.
To determine the contribution of specific environmental factors to different social values.

Main Methods:

Utilized the Social Values for Ecosystem Services (SolVES) model.
Employed MaxEnt for analyzing environmental variable contributions.
Assessed spatial distribution characteristics based on distance to water (DTW), distance to road (DTR), and landscape type (LT).

Main Results:

Environmental variables significantly influenced social value distribution: DTW created strip patterns, DTR concentrated values along roads, and LT localized values within landscapes.
Landscape type (LT) was the dominant factor when combined with DTW and DTR.
MaxEnt analysis revealed LT as the primary contributor to aesthetic (47.6%), therapeutic (50.5%), and historic (80.0%) values. DTW was the main contributor to recreation (43.1%).

Conclusions:

Environmental variables, particularly landscape type, significantly shape the spatial distribution of social values in urban riverfronts.
Understanding these relationships allows for targeted management strategies to enhance social benefits while minimizing ecological impact.
Sustainable management of urban riverfronts requires integrating social value assessment with environmental variable analysis to balance human needs and ecological integrity.