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Enhancing Ecological Education: Utilizing Agent-based Modeling to Simplify the Impacts of Deforestation on Amphibians

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding how deforestation and changes in habitat boundaries affect biodiversity is essential for developing conservation solutions. These topics are central to biology and ecology programs, where stu-dents learn to apply their knowledge in real-world conservation efforts. Higher education plays a crucial role in strengthening this understanding, particularly in life sciences programs. Given the complexity of ecological processes in altered landscapes, agent-based modeling provides an interactive and engaging way to simplify and visualize the effects of land use changes. In this study, we integrate Amazonian anurans, highly sensitive to temperature and humidity fluctuations, with an Agent-based model to simulate the impacts of deforestation, habitat restoration, and land abandonment on species survival and movement. Their ectothermic nature and dependence on pulmocutaneous respiration make them especially vulnerable to the drier and more variable con-ditions caused by deforestation. Integrating this model into conservation biology courses has enhanced learning by encouraging independent exploration, both in and out of the classroom. This tool, an agent-based model, is particularly suited for university-level ecology and conservation courses, and can also serve as an effective awareness tool in environmental education and decision-making workshops, highlighting the negative effects of human-made habitat changes on biodiversity.
Original languageEnglish
Pages (from-to)78-100
Number of pages23
JournalBIODIVERSITY INFORMATICS
Volume18
StatePublished - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Agent-based modeling
  • Edge effect
  • Education classroom
  • Landscape transformation

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