Environmental Research Letters · 2020 · 95 citations · 44 references
Social SciencesEnvironmental SciencesUrban StudiesUrban EcologyUrban Environmental StudiesUrban GeographyUrban Environmental ChangeUrban Environmental ExperienceUrban SustainabilityEcosystem ServicesEcosystem Services In CitiesHuman-nature Relations In CitiesUrban Biodiversity ConservationUrban Ecosystem ServicesUrban Ecosystem Services Assessment
Abstract The evidence base for the benefits of urban nature for people and biodiversity is strong. However, cities are diverse and the social and environmental contexts of cities are likely to influence the observed effects of urban nature, and the application of evidence to differing contexts. To explore biases in the evidence base for the effects of urban nature, we text-matched city names in the abstracts and affiliations of 14 786 journal articles, from separate searches for articles on urban biodiversity, the health and wellbeing impacts of urban nature, and on urban ecosystem services. City names were found in 51% of article abstracts and 92% of affiliations. Most large cities were studied many times over, while only a small proportion of small cities were studied once or twice. Almost half the cities studied also had an author with an affiliation from that city. Most studies were from large developed cities, with relatively few studies from Africa and South America in particular. These biases mean the evidence base for the effects of urban nature on people and on biodiversity does not adequately represent the lived experience of the 41% of the world’s urban population who live in small cities, nor the residents of the many rapidly urbanising areas of the developing world. Care should be taken when extrapolating research findings from large global cities to smaller cities and cities in the developing world. Future research should encourage research design focussed on answering research questions rather than city selection by convenience, disentangle the role of city size from measures of urban intensity (such as population density or impervious surface cover), avoid gross urban-rural dualisms, and better contextualise existing research across social and environmental contexts.
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