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基于 SolVES 模型的城市滨水空间生态系统服务社会价值评价——以西安市沣河为例。

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.

机构信息

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

Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, China.

出版信息

Int J Environ Res Public Health. 2021 Mar 9;18(5):2765. doi: 10.3390/ijerph18052765.

DOI:10.3390/ijerph18052765
PMID:33803264
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7967293/
Abstract

Urban riverfront space has diversified ecosystem services, but due to excessive changes in the geographical environment, such as drastic changes in land use, people gain social value at a great ecological cost. Obtaining benefits from the ecosystem in this way is not sustainable. Therefore, this paper uses the SolVES model to evaluate the social value of ecosystem services on the east bank of the Fenghe River, while also studying the contribution of different environmental variables to social value. The main results are as follows. (1) Environmental variables affect the spatial distribution characteristics of social value. The distance to water (DTW) means the social value was distributed in strips, and the distance to road (DTR) concentrated the social value along the road. The landscape type (LT) means the social value was concentrated in the landscape space. (2) When DTW, DTR, and LT were collectively used as environmental variables, the distribution characteristics of various social values were similar to when LT was used as the only environmental variable. (3) The results of MaxEnt show that LT made a greater contribution to the aesthetic, recreation, therapeutic, and historic values, and was the largest contribution factor to the aesthetic, therapeutic, and historic values, with contribution rates of 47.6, 50.5, and 80.0%, respectively. DTW is the factor that contributed the most to recreation, with a contribution rate of 43.1%. Improving social value based on the influence and contribution of environmental variables can reduce the damage to the ecological environment caused by changes in geographic factors. This is sustainable for both the ecosystem and the services it provides to mankind.

摘要

城市滨河空间具有多样化的生态系统服务功能,但由于地理环境的过度变化,如土地利用的剧烈变化,人们以巨大的生态代价获得了社会价值。以这种方式从生态系统中获取利益是不可持续的。因此,本文利用 SolVES 模型评估丰河河东岸的生态系统服务的社会价值,同时研究不同环境变量对社会价值的贡献。主要结果如下。(1)环境变量影响社会价值的空间分布特征。距水距离(DTW)意味着社会价值呈带状分布,距路距离(DTR)则使社会价值集中在道路沿线。景观类型(LT)意味着社会价值集中在景观空间。(2)当 DTW、DTR 和 LT 被共同用作环境变量时,各种社会价值的分布特征与仅使用 LT 作为唯一环境变量时相似。(3)MaxEnt 的结果表明,LT 对美学、娱乐、治疗和历史价值的贡献更大,对美学、治疗和历史价值的贡献最大,贡献率分别为 47.6%、50.5%和 80.0%。DTW 是对娱乐贡献最大的因素,贡献率为 43.1%。基于环境变量的影响和贡献来提高社会价值,可以减少地理因素变化对生态环境造成的破坏。这对生态系统及其为人类提供的服务都是可持续的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/5aceb88accf1/ijerph-18-02765-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/21904f41f3b4/ijerph-18-02765-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/d3ef2a1efc8f/ijerph-18-02765-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/c71191a869b3/ijerph-18-02765-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/731c29d7a3dd/ijerph-18-02765-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/ed7adafa2f7e/ijerph-18-02765-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/135765c859f3/ijerph-18-02765-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/8fb3e9603884/ijerph-18-02765-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/1059309ca5c4/ijerph-18-02765-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/a3199b9e380b/ijerph-18-02765-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/5aceb88accf1/ijerph-18-02765-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/21904f41f3b4/ijerph-18-02765-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/d3ef2a1efc8f/ijerph-18-02765-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/c71191a869b3/ijerph-18-02765-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/731c29d7a3dd/ijerph-18-02765-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/ed7adafa2f7e/ijerph-18-02765-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/135765c859f3/ijerph-18-02765-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/8fb3e9603884/ijerph-18-02765-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/1059309ca5c4/ijerph-18-02765-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/a3199b9e380b/ijerph-18-02765-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b1/7967293/5aceb88accf1/ijerph-18-02765-g009.jpg

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