Coastal Sciences, Gulf Coast Research Laboratory
Biogeochemical models that simulate realistic lower-trophic-level dynamics, including the representation of main phytoplankton and zooplankton functional groups, are valuable tools for improving our understanding of natural and anthropogenic disturbances in marine ecosystems. Pre- vious three-dimensional biogeochemical modeling studies in the northern and deep Gulf of Mexico (GoM) have used only one phytoplankton and one zooplankton type. To advance our modeling capability of the GoM ecosystem and to investigate the dominant spatial and seasonal patterns of phytoplank- ton biomass, we configured a 13-component biogeochemical model that explicitly represents nanophytoplankton, diatoms, micro-, and mesozooplankton. Our model outputs compare reasonably well with observed patterns in chlorophyll, pri- mary production, and nutrients over the Louisiana–Texas shelf and deep GoM region. Our model suggests silica limi- tation of diatom growth in the deep GoM during winter and near the Mississippi delta during spring. Model nanophyto- plankton growth is weakly nutrient limited in the Mississippi delta year-round and strongly nutrient limited in the deep GoM during summer. Our examination of primary produc- tion and net phytoplankton growth from the model indicates that the biomass losses, mainly due to zooplankton grazing, play an important role in modulating the simulated seasonal biomass patterns of nanophytoplankton and diatoms. Our analysis further shows that the dominant physical process in- fluencing the local rate of change of model phytoplankton is horizontal advection in the northern shelf and vertical mixing in the deep GoM. This study highlights the need for an inte- grated analysis of biologically and physically driven biomass fluxes to better understand phytoplankton biomass phenolo- gies in the GoM.
Gomez, F. A.,
Hernandez Jr., F.,
Muller-Karger, F. E.,
Lamkin, J. T.
(2018). Seasonal Patterns in Phytoplankton Biomass Across the Northern and Deep Gulf of Mexico: A Numerical Model Study. Biogeosciences, 15, 3561-3576.
Available at: https://aquila.usm.edu/fac_pubs/15437