A review on the progress of modeling techniques in ecosystem services

Ting, 李婷 Li; Yihe, 吕一河 Lü

doi:10.5846/stxb201708291562

Cited by 4 publications

(2 citation statements)

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“…Assessing urban ecosystem services often involves multiple systems with a high degree of interactions, but the understanding of the complex system often lacks theory and enough data to support; expert-based models are semi-quantitative ways which can simulate and predict it with interdisciplinary knowledge [36]. Social ecological scenarios analysis and Bayesian network are common methods.…”

Section: Classification Of Modelling Techniques For Ecosystem Servicesmentioning

confidence: 99%

Models for Assessing Urban Ecosystem Services: Status and Outlooks

Ouyang

Luo

2022

Sustainability

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Urban ecosystem services provide many benefits for human beings. Given the dramatic increase of urbanization, maintaining sustainability of cities relies heavily on ecosystem services, and it is crucial for quantifying, managing, and optimizing urban ecosystem services to promote social and ecological sustainable development. This study presents the review of models for assessing urban ecosystem services through gathering the pertinent literatures which were published recent years. The main types of approaches for assessing urban ecosystem services were summarized, and the model simulation approach was detailed. From modelling techniques to the existing models, it was found that a process-based model is, relatively, a better way to detect the mechanism of urban ecological processes and simulate the future dynamic changes of urban ecosystem services. Three key limitations of existing products and frameworks were identified: (1) lacking understanding of multiple urban ecosystem services interactions, (2) ignoring accounting the socioeconomic factors into dynamics of urban ecosystem, and (3) lacking considerations of feedback effects between social system and urban ecosystem. The study concludes with outlooks that a comprehensive social-ecosystem model based on the social-ecological framework is helpful to reveal the relationships and interactions among various urban ecosystem services, and can better assess how human-induced urban growth affects ecosystem services, and better describe the feedback effect between the social environment and urban ecosystem services, as well as dynamically predict the changes of urban ecosystem services under different scenarios in future long time series.

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Section: Classification Of Modelling Techniques For Ecosystem Servicesmentioning

confidence: 99%

Models for Assessing Urban Ecosystem Services: Status and Outlooks

Ouyang

Luo

2022

Sustainability

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“…In particular, the functional value assessment method evaluated some key service functions through a series of biological equations and parameters, such as food production, carbon sequestration, oxygen production, water conservation, soil conservation, recreation, and habitat provision [10][11][12][13]. Although this method can measure the number of service functions more accurately, the calculation process is complicated and can bring uncertainty to the assessment if it lacks a careful consideration of the regional ecological background [4,14]. The equivalent factor assessment method can directly link regional land use and ecological quality [15,16].…”

Section: Introductionmentioning

confidence: 99%

Identifying Driving Factors of Basin Ecosystem Service Value Based on Local Bivariate Spatial Correlation Patterns

Ding

Shu

Tang

et al. 2022

Land

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Ecosystem service value (ESV) is a crucial indicator for evaluating ecosystem health, and identifying its spatial driving factors will help to provide scientific decision support for ecological protection and restoration. This study took the Liuxi River Basin in China as the research object and used the value equivalent method to estimate regional ESV. In the process of using the Geodetector model (GDM), the study area was spatially stratified by using the local bivariate spatial correlation pattern to mine the potential driving factors of ESV. The results show that: (1) From 2005 to 2018, the total value of ecosystem services in the Liuxi River Basin showed a fluctuating and increasing trend. ESV had high-value aggregation in the northeastern mountainous areas with high green space coverage and high river distance accessibility and low-value aggregation in the central and southwestern urban areas with frequent human activities. Its spatial heterogeneity and aggregation patterns were of statistical significance. (2) The spatial distribution characteristics of ESV were affected by various driving factors to varying degrees. The order of their degree of influence on ESV was per capita green area > slope > the proportion of urban and rural human settlements > river distance accessibility > population. (3) Compared to the previous study, the stratification method employing the local bivariate spatial correlation pattern more fully considers spatial autocorrelation and spatial heterogeneity. It effectively captured the spatial explanatory power of driving factors. This study can provide new ideas for capturing the driving mechanisms of ESV and insights into the sustainable development of the ecological environment in other regions with similar characteristics worldwide.

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