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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Title
Species distribution modeling of seagrass in the Gulf of Mexico
Resource Type
Poster
Event
Summer Undergraduate Research Program (University of West Florida, Pensacola, Florida, 2021)
Contributors
Zhiyong Hu (Faculty Mentor)
Publisher
University of West Florida Libraries; Argo Scholar Commons
Format
pdf
Copyright
Permission granted to the University of West Florida Libraries to digitize and/or display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder.
Identifiers
99380090790306600
Academic Unit
Summer Undergraduate Research Program 2021
Language
English
Species distribution modeling of seagrass in the Gulf of Mexico