Wealth and Education Influences on Spatial Pattern of Tree Planting in a Tropical Metropolis in Brazil

Environ Manage. 2022 Jan;69(1):169-178. doi: 10.1007/s00267-021-01542-2. Epub 2021 Sep 28.

Abstract

Green infrastructure, and specifically urban afforestation, is one of the most important activities of city management today, because of the multitude of ecosystem services it provides. The pattern of tree planting in urban areas is related to age, ethnicity, education, and household income. Unfortunately, this issue has not been evaluated, nor has it received significant subsidized governmental actions, funding, study, or public policies in large tropical cities in developing countries. Thus, we aimed to investigate if there was a pattern of urban afforestation related by socio-territorial inequalities, in the city of São Paulo, or if there was a relationship between the number of seedlings planted over the past 4 years and zoning, socioeconomic, health, and environment variables in the neighborhoods of São Paulo, as well as to evaluate the ecosystem services provided by the planted species. Our results showed that tree planting was not oriented to increase cover of less-vegetated areas of the city and where more respiratory diseases have been registered. In fact, the number of seedlings planted over the past 4 years was very influenced by socioeconomic status of inhabitants. In this sense, wealth and education proved to be a better predictor than zoning, health, and environmental variables for the tree planting. Finally, our results reveal that supporting, provision, and cultural functions and services are being provided to São Paulo city by the selected woody species. In Sao Paulo, urban afforestation must extend to the neighborhoods that need the services the most.

Keywords: Developing country; Ecosystem services; Environmental policy; Landscape architecture; Urban afforestation; Urban planning.

MeSH terms

  • Brazil
  • Cities
  • City Planning
  • Demography
  • Ecosystem*
  • Socioeconomic Factors
  • Trees*