Species distribution modeling of seagrass in the Gulf of Mexico

Seagrass meadows function as vital underwater ecosystems integral to biological, chemical, and physical process dynamics. We generated classification estimates for potential (predicted)
environmental range (PER) of seagrass distribution within shelf areas of the Gulf of Mexico using random forest modeling, a supervised machine learning method. The model identified
sediment grain size, median bottom shear stress, silicate, nitrate, and phosphate as being the most important environmental drivers.
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Abstract/Description: Seagrass meadows function as vital underwater ecosystems integral to biological, chemical, and physical process dynamics. We generated classification estimates for potential (predicted) environmental range (PER) of seagrass distribution within shelf areas of the Gulf of Mexico using random forest modeling, a supervised machine learning method. The model identified sediment grain size, median bottom shear stress, silicate, nitrate, and phosphate as being the most important environmental drivers.
Subject(s): Undergraduate Research
Date Issued: 2021