A scenario-driven strategy for future habitat management of the Andean bear

Authors

  • Ahmet Acarer Department of Wildlife Ecology and Management, Faculty of Forestry, Isparta Applied Sciences University, Isparta, Türkiye

DOI:

https://doi.org/10.5281/zenodo.13822908

Keywords:

Andean bear, Chelsa climate, modeling and mapping, planning, wildlife

Abstract

Today, climate adaptation strategies are at the forefront in wildlife management and protection studies. This study aimed to model and map the effects of global climate change on the Andean bear, which is in the vulnerable category and distributed in South America. For this purpose, 20 environmental variables and 19 high-resolution Chelsa climate maps that could be effective on Andean bear modeling were created. Moreover, the Maximum Entropy method, which is frequently preferred in species distribution modeling, was preferred. The current habitat suitability model of the Andean bear was in the “very good” model category with the training data set ROC value of 0.973 and the test data set ROC value of 0.972. The variables contributing to the current model are roughness index (41.1%), isothermality (38%), elevation (14%), and annual mean temperature (6.9%), respectively. Variables contributing to the current Andean bear model have been simulated in different scenarios (SSP126/SSP370/SSP585) for the year 2100. However, it has been determined that Andean bear habitats will shrink according to the SSP126 Chelsa climate scenario of the year 2100, these habitats will fragment according to the SSP370 scenario, and brown bear habitats will disappear in some regions in the SSP585 scenario. In conclusion, this study raises alarms that the possible decrease in Andean bear habitats will be approximately 67.3% by the year 2100 due to global climate change.

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Published

2024-09-16

How to Cite

Acarer, A. (2024). A scenario-driven strategy for future habitat management of the Andean bear. Journal of Wildlife and Biodiversity, 8(4), 56–77. https://doi.org/10.5281/zenodo.13822908