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Yeast Colony Embedding Method

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Published on: March 22, 2011

Saccharomycotina yeasts defy long-standing macroecological patterns.

Kyle T David^1,2, Marie-Claire Harrison^1,2, Dana A Opulente^3,4

¹Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235.

Proceedings of the National Academy of Sciences of the United States of America

|February 27, 2024

Summary

This summary is machine-generated.

This study maps global yeast distributions using machine learning, revealing hotspots in temperate forests. Yeast ranges are shaped by environmental factors, challenging traditional macroecological rules.

Keywords:

AI biogeography fungi latitudinal species gradient macroecology

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Area of Science:

Mycology
Macroecology
Computational Biology

Background:

The Saccharomycotina yeasts are ecologically diverse but their global distribution rules are poorly understood.
Understanding yeast biogeography is crucial for ecological, economic, and medical applications.

Purpose of the Study:

To model global yeast species distributions at high resolution (~1 km²).
To identify key environmental drivers of yeast biogeography and macroecology.
To test how yeast distributions conform to or contravene established macroecological principles.

Main Methods:

Trained machine learning models on 12,816 terrestrial occurrence records.
Utilized 96 environmental variables to infer global distribution maps for 186 yeast species.
Analyzed environmental drivers and range limit influences.

Main Results:

Predicted yeast diversity hotspots in temperate mixed montane forests.
Vegetation type and topography significantly predict yeast species richness.
Yeast range limits are influenced by carbon niche breadth and interspecific overlap.
Yeasts challenge macroecological principles like the latitudinal diversity gradient and Rapoport's rule.

Conclusions:

Environmental factors, particularly microhabitats and environmental clines, are key drivers of yeast diversity and distribution.
High-resolution distribution models aid in predicting economically relevant and pathogenic yeast species under climate change.
This research provides novel insights into the macroecology of a globally significant fungal clade.