Anthropogenic pressure and protected areas in the Brazilian Atlantic Forest: Serra da Tiririca State Park process and patterns

Felipe Zuñe, Pablo José Francisco Pena Rodrigues, Cassia Mônica Sakuragui, Andrea Ferreira da Costa, Guillermo Eduardo Delgado-Paredes, Márcia Gonçalves Rogério, Nilber Gonçalves da Silva

Research output: Contribution to journalArticlepeer-review

Abstract

Protected areas are key to biodiversity conservation and essential to ecosystem services. However, anthropogenic pressures, such as human population growth, and environmental factors, such as temperature and precipitation changes, have caused intense modifications in these areas, especially in the Atlantic Forest, a biodiversity hotspot. This study aimed to describe changes in land use and land cover (LULC) over 38 years in a protected area of the Atlantic Forest and assess the effects of anthropogenic and environmental factors on LULC cover dynamics. We explored mapping data from the MapBiomas, for the period between 1985 and 2022, and correlated these data to variables of human population density, temperature and precipitation by using generalized linear models. We observed that forest formations and restingas increased their coverage by 2.99% and 20.68%, respectively. In contrast, wetlands, rocky outcrops, farming, sandy areas, urban areas and water bodies decreased in coverage by around 28.11%. The increase in human population density outside the protected area is the main driver of changes in LULC in PESET. Predictions from the models showed that sandy areas are likely to disappear within ten years. Our study shows that even protected areas remain vulnerable to human actions and subject to significant changes in the future.

Original languageEnglish
Article numbere20241658
JournalBiota Neotropica
Volume25
Issue number2
DOIs
StatePublished - 2025

Bibliographical note

Publisher Copyright:
© 2025, Universidade Estadual de Campinas UNICAMP. All rights reserved.

Keywords

  • Biodiversity Conservation
  • Land Use and Land Cover
  • Population Density
  • Remote Sensing
  • Rio de Janeiro

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