Combined Generalized Additive model and Random Forest to evaluate the influence of environmental factors on phytoplankton biomass in a large eutrophic lake

Combined Generalized Additive model and Random Forest to evaluate the influence of environmental factors on phytoplankton biomass in a large eutrophic lake

The over-proliferation of phytoplankton has been a public concern for the last several decades. To evaluate the importance of different environmental factors on phytoplankton biomass variations with their complex response relationships in the large eutrophic Lake Okeechobee, the nonlinear methods in...

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Bibliographic Details
Main Authors: Zhang, J. (Author), Zhang, Y. (Author), Zhi, M. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
Additives
algal bloom
algorithm
biomass
Biomass
Decision trees
environmental factor
Environmental factors
eutrophic environment
Eutrophic lakes
Eutrophication
Florida [United States]
Generalized additive model
Generalized Additive Model
Lake Okeechobee
Lakes
light availability
Local scale
Model forests
numerical model
Nutrients
phytoplankton
Phytoplankton
Phytoplankton biomass
Quality control
Quality management
Random Forest
Random forests
Spatial heterogeneity
Total nitrogen
United States
Water conservation
Water management
Water quality
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