Creating better cities: how biodiversity and ecosystem functioning enhance urban residents’ wellbeing

Taylor, Lucy; Hochuli, Dieter F.

doi:10.1007/s11252-014-0427-3

Cited by 120 publications

(79 citation statements)

References 99 publications

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“…Green space itself may take many forms, and it may be that the association with mental wellbeing depends on the type rather amount of green space [74, 75]. Similarly, previous studies have shown that the quality of green space, and its biodiversity, were positively associated with mental health, where quantity was found to be less significant [76].…”

Section: Discussionmentioning

confidence: 99%

A cross-sectional analysis of green space prevalence and mental wellbeing in England

2017

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BackgroundWith urbanisation increasing, it is important to understand how to design changing environments to promote mental wellbeing. Evidence suggests that local-area proportions of green space may be associated with happiness and life satisfaction; however, the available evidence on such associations with more broadly defined mental wellbeing in still very scarce. This study aimed to establish whether the amount of neighbourhood green space was associated with mental wellbeing.MethodsData were drawn from Understanding Society, a national survey of 30,900 individuals across 11,096 Census Lower-Layer Super Output Areas (LSOAs) in England, over the period 2009–2010. Measures included the multi-dimensional Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) and LSOA proportion of green space, which was derived from the General Land Use Database (GLUD), and were analysed using linear regression, while controlling for individual, household and area-level factors.ResultsThose living in areas with greater proportions of green space had significantly higher mental wellbeing scores in unadjusted analyses (an expected increase of 0.17 points (95% CI 0.11, 0.23) in the SWEMWBS score for a standard deviation increase of green space). However, after adjustment for confounding by respondent sociodemographic characteristics and urban/rural location, the association was attenuated to the null (regression coefficient B = − 0.01, 95% CI -0.08, 0.05, p = 0.712).ConclusionsWhile the green space in an individual’s local area has been shown through other research to be related to aspects of mental health such as happiness and life satisfaction, the association with multidimensional mental wellbeing is much less clear from our results. While we did not find a statistically significant association between the amount of green space in residents’ local areas and mental wellbeing, further research is needed to understand whether other features of green space, such as accessibility, aesthetics or use, are important for mental wellbeing.

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Section: Discussionmentioning

confidence: 99%

A cross-sectional analysis of green space prevalence and mental wellbeing in England

2017

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“…Recently, other methods based on ecosystem services have received attention, wherein each green infrastructure patch serves to identify GI elements. This method is mainly used to evaluate the coupling relationship between green infrastructure and ecosystem services, and it requires a large amount of supporting data [17,[21][22][23][24][25]. Table 1.…”

Section: Introductionmentioning

confidence: 99%

Research on the Optimization of Regional Green Infrastructure Network

Shi

Qin

2018

Sustainability

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With the rapid rate of urbanization, green infrastructure land is increasingly being converted to urban construction land, and the fragmentation of regional green infrastructure (GI) networks is intensifying. The connectivity of a GI network is of paramount importance for maintaining both regional biodiversity and regional ecosystem service capacity, among others. In this paper, an innovative approach to planning a GI network is presented. The proposed approach is based on the Morphological Spatial Pattern Analysis (MSPA) method, minimum path method, and circuit theory. Using the Zhengzhou–Kaifeng metropolitan area in China as a case study, we argue that the combination of the MSPA method and circuit theory can more fully and comprehensively identify the components of a GI network and its key areas. The methodology consists of three steps: (i) Identifying the cores and bridges of the GI by the MSPA method based on land use data, followed by determining the hubs of the GI network by assessing the connectivity of the core area; (ii) establishing potential connecting corridors between hubs by the minimum path method; (iii) identifying the “pinch point” area of the potential connecting corridors based on current density by applying circuit theory. This approach not only makes identification of the “hubs” and “links” in the green infrastructure network more scientific and comprehensive, but it also further identifies “pinch point” areas of the connecting corridors that require priority protection or recovery. The research results can be used as a practical reference for urban planners when planning urban land use.

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“…Under such circumstances, effectively evaluating the impact of land use changes on ecosystem services has become a matter of global concern, and it is urgently required to provide support for policy making that could mitigate its negative effects on the ecology and promote regional sustainable development [7]. Since the implementation of the Millennium Ecosystem Assessment (MEA) project in 2001, an increasing number of studies have been conducted that demonstrate that urbanization induced land use change is becoming a significant contributor of variation in ecosystem services [6,8].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Spatiotemporally Varying Correlation between Urban Spatial Patterns and Ecosystem Services: A Case Study of Nansihu Lake Basin, China

Zhao

2019

IJGI

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Ecosystem services are the benefits obtained from an ecosystem that have great significance in sustainable development. Urbanization has triggered significant changes on urban spatial patterns, which have had a great impact on the ecosystem services. However, studies on the spatiotemporally varying relationship between urban spatial patterns and ecosystem services are lacking. Taking as a case study, the Nansihu Lake Basin in China, this study aimed to explore the spatiotemporally varying relationship between urban spatial patterns and ecosystem services. Urban spatial patterns were derived by integrating remote sensing and spatial metrics. Ecosystem service values were calculated using ecosystem service models. The spatiotemporally varying impact of urban spatial patterns on ecosystem services was quantified using the Geographically Weighted Regression (GWR) model. The findings indicate that urban spatial patterns and ecosystem services have dramatically varied with the urbanization process. The estimated parameters indicate that urban spatial patterns have significant impacts on ecosystem services. The GWR revealed a spatiotemporally varying correlation and improved the explanatory ability in comparison with the Ordinary Least Squares (OLS) model. The investigation of the impact of urban spatial patterns on ecosystem services can provide more practical support for effective urban planning and ecosystem management.

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Creating better cities: how biodiversity and ecosystem functioning enhance urban residents’ wellbeing

Cited by 120 publications

References 99 publications

A cross-sectional analysis of green space prevalence and mental wellbeing in England

A cross-sectional analysis of green space prevalence and mental wellbeing in England

Research on the Optimization of Regional Green Infrastructure Network

Investigating the Spatiotemporally Varying Correlation between Urban Spatial Patterns and Ecosystem Services: A Case Study of Nansihu Lake Basin, China

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