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Evidence from eleven countries in four continents suggests that protected areas are not associated with higher poverty rates

Christos Mammides

Published 2020 in Biological Conservation

ABSTRACT

Abstract Countries across the globe are expanding their networks of protected areas in an effort to address the increasing rates of biodiversity loss. Protected areas, though, have been criticized extensively for their negative impact on the local communities. Case studies have shown that protected areas can exacerbate poverty. However, these case studies represent only a small proportion of the over two-hundred thousand protected areas available worldwide today. Hence, it is possible that most protected areas do not impoverish the local communities. In fact, a few recent studies have suggested that protected areas do not impact negatively the local people. The findings of those studies, however, are based predominately on data from small geographical regions. Consequently, it is unclear whether their results are widely applicable. In this study, I have used a large dataset from 5800 administrative regions in eleven countries and four continents to explore in more detail the link between protected areas and local poverty rates. Particularly, I have used the quasi-experimental matching method to test whether administrative regions with protected areas have higher proportions of people living below the poverty line. I found no evidence to support this pattern. Protected areas do not appear to be associated with higher poverty rates. Considering that, firstly, biodiversity conservation and poverty alleviation represent two of the most urgent challenges of our time, and, secondly, that most efforts to conserve biodiversity are channeled through protected areas, it is crucial to know that protected areas do not interfere with our efforts to alleviate poverty.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Biological Conservation

  • Publication date

    Unknown publication date

  • Fields of study

    Geography, Sociology, Economics, Environmental Science

  • Identifiers
    DOI 10.1016/j.biocon.2019.108353
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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