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作者

来源

LANDSCAPE AND URBAN PLANNING,Vol.170,P.293-308

语言

英文

关键字

Meta-analysis; Urban forests; Environmental inequity; Environmental justice; NEW-YORK-CITY; QUALITY-OF-LIFE; ENVIRONMENTAL JUSTICE; TREE COVER; STREET TREES; LAND-COVER; SOCIOECONOMIC CONDITIONS; SPATIAL-DISTRIBUTION; SOCIAL-INEQUALITY; GROUP IDENTITY

作者单位

[Gerrish, Ed] Univ South Dakota, 414 E Clark St, Vermillion, SD 57069 USA. [Watkins, Shannon Lea] Univ Calif San Francisco, 530 Parnassus Ave, San Francisco, CA 94143 USA. Watkins, SL (reprint author), Univ Calif San Francisco, 530 Parnassus Ave, San Francisco, CA 94143 USA. E-Mail: ed.gerrish@usd.edu; shannon.watkins@ucsf.edu

摘要

Urban trees provide substantial public health and public environmental benefits. However, scholarly works suggest that urban trees may be disproportionately low in poor and minority urban communities, meaning that these communities are potentially being deprived of public environmental benefits, a form of environmental injustice. The evidence of this problem is not uniform however, and evidence of inequity varies in size and significance across studies. This variation in results suggests the need for a research synthesis and meta-analysis. We employed a systematic literature search to identify original studies which examined the relationship between urban forest cover and income (n = 61) and coded each effect size (n = 332). We used meta-analytic techniques to estimate the average (unconditional) relationship between urban forest cover and income and to estimate the impact that methodological choices, measurement, publication characteristics, and study site characteristics had on the magnitude of that relationship. We leveraged variation in study methodology to evaluate the extent to which results were sensitive to methodological choices often debated in the geographic and environmental justice literature but not yet evaluated in environmental amenities research. We found evidence of income-based inequity in urban forest cover (unconditional mean effect size = 0.098; s.e. = 0.017) that was robust across most measurement and methodological strategies in original studies. and results did not differ systematically with study site characteristics. Studies that controlled for spatial autocorrelation, a violation of independent errors, found evidence of substantially less urban forest inequity; future research in this area should test and correct for spatial autocorrelation.