Created By:

Juliet  Fisk Alozie & Justin Freeman
University & Alabama State University
MS-CC Summer Research Internship

• Introduction to ecosystem disruption and mammals
• Project goals
• Machine learning approach
• Results summary
• Methodology overview
• Key Takeaways and limitations
• Future directions
• Q&A

Did you know that polar bears rely on cold climates and sea ice to hunt? As global temperatures rise and weather patterns shift, ecosystems worldwide are being disrupted. These changes, like increasing heat, altered rainfall, and more extreme weather, can damage natural habitats and interfere with how species migrate, reproduce, and survive. While conservation scientists have traditionally used fieldwork and statistical models to monitor biodiversity loss, these methods often
fall short in capturing the full scale and complexity of environmental change.

To address this, our project combined climatology, ecology, and machine learning to better understand how long-term climate variability affects mammal populations. Using the PanTheria dataset, we applied Random Forest models, an advanced machine learning approach that builds and combines multiple decision trees to uncover patterns between species traits, climate variables, and biodiversity loss. Our findings aimed to support more proactive conservation efforts and inform effective environmental policy planning.