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Modelling Climate Change Impacts on Tropical Dry Forest Fauna

Author

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  • Kimberly Stephenson

    (School of Environmental Sciences, University of Guelph, 50 Stone Rd E., Guelph, ON N1G 2W1, Canada
    Climate Studies Group Mona (CSGM), Department of Physics, University of the West Indies, Kingston 7, Jamaica
    Department of Life Sciences, University of the West Indies, Kingston 7, Jamaica)

  • Byron Wilson

    (Department of Life Sciences, University of the West Indies, Kingston 7, Jamaica)

  • Michael Taylor

    (Climate Studies Group Mona (CSGM), Department of Physics, University of the West Indies, Kingston 7, Jamaica)

  • Kurt McLaren

    (Department of Life Sciences, University of the West Indies, Kingston 7, Jamaica
    Department of Geography and Environmental Sciences, Northumbria University, Ellison Place, Newcastle upon Tyne NE1 8ST, UK)

  • Rick van Veen

    (Department of Life Sciences, University of the West Indies, Kingston 7, Jamaica)

  • John Kunna

    (Department of Life Sciences, University of the West Indies, Kingston 7, Jamaica)

  • Jayaka Campbell

    (Climate Studies Group Mona (CSGM), Department of Physics, University of the West Indies, Kingston 7, Jamaica)

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.

Suggested Citation

  • Kimberly Stephenson & Byron Wilson & Michael Taylor & Kurt McLaren & Rick van Veen & John Kunna & Jayaka Campbell, 2022. "Modelling Climate Change Impacts on Tropical Dry Forest Fauna," Sustainability, MDPI, vol. 14(8), pages 1-24, April.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4760-:d:795059
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    References listed on IDEAS

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    1. Camilo Mora & Abby G. Frazier & Ryan J. Longman & Rachel S. Dacks & Maya M. Walton & Eric J. Tong & Joseph J. Sanchez & Lauren R. Kaiser & Yuko O. Stender & James M. Anderson & Christine M. Ambrosino , 2013. "The projected timing of climate departure from recent variability," Nature, Nature, vol. 502(7470), pages 183-187, October.
    2. Stephen J. Fain & Maya Quiñones & Nora L. Álvarez-Berríos & Isabel K. Parés-Ramos & William A. Gould, 2018. "Climate change and coffee: assessing vulnerability by modeling future climate suitability in the Caribbean island of Puerto Rico," Climatic Change, Springer, vol. 146(1), pages 175-186, January.
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    Cited by:

    1. Julio Campo & Christian P. Giardina & Rodolfo Dirzo, 2023. "Tropical Dry Forest Restoration in an Era of Global Change: Ecological and Social Dimensions," Sustainability, MDPI, vol. 15(4), pages 1-5, February.

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