Modelling Climate Change Impacts on Tropical Dry Forest Fauna

Kimberly Stephenson*, Byron Wilson, Michael Taylor, Kurt McLaren, Rick Van Veen, John Kunna, Jayaka Campbell

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    8 Citations (Scopus)
    37 Downloads (Pure)

    Abstract

    Tropical dry forests are among the most threatened ecosystems in the world, and those occurring in the insular Caribbean are particularly vulnerable. Climate change represents a significant threat for the Caribbean region and for small islands like Jamaica. Using the Hellshire Hills protected area in Jamaica, a simple model was developed to project future abundance of arthropods and lizards based on current sensitivities to climate variables derived from rainfall and temperature records. The abundances of 20 modelled taxa were predicted more often by rainfall variables than temperature, but both were found to have strong impacts on arthropod and lizard abundance. Most taxa were projected to decrease in abundance by the end of the century under drier and warmer conditions. Where an increase in abundance was projected under a low emissions scenario, this change was reduced or reversed under a high emissions climate change scenario. The validation process showed that, even for a small population, there was reasonable skill in predicting its annual variability. Results of this study show that this simple model can be used to identify the vulnerability of similar sites to the effects of shifting climate and, by extension, their conservation needs.
    Original languageEnglish
    Article number4760
    Number of pages24
    JournalSustainability
    Volume14
    Issue number8
    DOIs
    Publication statusPublished - 15 Apr 2022

    UN SDGs

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

    1. SDG 13 - Climate Action
      SDG 13 Climate Action
    2. SDG 15 - Life on Land
      SDG 15 Life on Land

    Keywords

    • tropical dry forest
    • biodiversity
    • bioclimatic modelling
    • Caribbean

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