城市森林与收入关系的元分析

E. Gerrish, S. Watkins
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引用次数: 126

摘要

城市树木提供了巨大的公共健康和公共环境效益。然而,学术研究表明,城市树木可能在贫困和少数民族城市社区中分布不均,这意味着这些社区可能被剥夺了公共环境利益,这是一种环境不公正的形式。然而,这一问题的证据并不统一,不同研究中不平等的证据在规模和重要性上各不相同。结果的这种差异表明需要进行研究综合和荟萃分析。我们采用了系统的文献检索,以确定研究城市森林覆盖与收入之间关系的原始研究(n=61),并对每个效应大小(n=332)进行编码。我们使用元分析技术来估计城市森林覆盖与收入之间的平均(无条件)关系,并估计方法选择、测量、出版物特征和研究地点特征对这种关系的影响程度。我们利用研究方法的变化来评估结果对方法选择的敏感程度,这些方法选择经常在地理和环境正义文献中争论,但尚未在环境便利研究中进行评估。我们发现城市森林覆盖存在基于收入的不平等(无条件平均效应值= 0.098;s.e. = 0.017),在原始研究中的大多数测量和方法学策略中都是稳健的,结果与研究地点的特征没有系统差异。控制空间自相关性(违反独立误差)的研究发现,有证据表明,城市森林的不平等程度大大降低;未来的研究应该对空间自相关进行检验和校正。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Relationship between Urban Forests and Income: A Meta-Analysis
Urban trees provide substantial public health and public environmental benefits. However, scholarly works suggest that urban trees may be unequally distributed among 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. = .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.
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