In partial fulfillment of the requirements for the degree of

 

Doctor of Philosophy in Biology

In the

School of Biological Sciences

 

ZAINAB ALRIYAMI

 

Will defend her dissertation

 

Spatial and Temporal Variation in

Primary Productivity 
in the Western Tropical North Atlantic: 
Experimental and Stable Isotope Approaches

 

 

4, November 2024

TIME 12 PM

 

https://gatech.zoom.us/j/99370284763

 

Thesis Advisor:

Joseph Montoya, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Committee Members:

Mark Hay, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Jennifer Glass, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Ito Taka, Ph.D.

School of Earth and Atmospheric Sciences

Georgia Institute of Technology

 

Joel Kostka, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

 

ABSTRACT:

Phytoplankton photosynthesis, which converts inorganic carbon into organic matter, is the foundational process fueling marine ecosystems. This primary productivity supports the growth and metabolic needs of higher trophic levels. It plays a critical role in regulating the global carbon cycle by facilitating carbon dioxide removal from the atmosphere over longer time scales. Studying these dynamic biological processes is essential to understanding and predicting the impacts of environmental changes on marine ecosystems. We can unravel the complexities of this vital process by employing experimental and natural abundance measurements that capture both instantaneous and time-integrated processes.

My research focused on the Western Tropical North Atlantic (WTNA), a region significantly influenced by the Amazon River Plume (ARP). The ARP creates a distinctive environment where freshwater from the Amazon River mixes with oceanic waters, leading to unique nutrient dynamics, light conditions, and phytoplankton distributions. This study explored the spatial variations (using a novel habitat delineation approach) and temporal changes ( using field data from three distinct seasons) in primary production and biomass within this region. I utilized a combination of direct observational data, experimental rate measurements, satellite data, modeling, and the natural abundance of carbon stable isotope analysis, complemented with advanced statistical analysis.

Using 13C tracer techniques, we measured phytoplankton growth and carbon fixation rates across different habitats and seasons within the ARP region. The results uncovered significant seasonal and regional variations in productivity, with peak carbon fixation rates occurring in the plume core during high discharge periods. Large phytoplankton cells dominated production in the nutrient-rich, mesohaline plume-core areas, showing lateral contrasts among habitats across different seasons, while smaller cells prevailed in nutrient-poor offshore waters. The photosynthetic efficiency of phytoplankton varied substantially across the ARP, with the highest light-saturated growth and production rates in the plume core and lower rates offshore.

In addition to measuring instantaneous carbon fixation rates (on the scale of one day), we utilized carbon stable isotope analysis of suspended particles, capturing a time scale of approximately one week, to trace organic carbon sources within the ARP. This approach allows us to evaluate the extent of phytoplankton influence on the ecosystem across a broad range of temporal scales. These data revealed a strong terrestrial influence near the river mouth, characterized by more negative δ13C values and higher C:N ratios. As the plume extended offshore, the influence of marine processes became more pronounced, as reflected by higher δ13C values and lower C:N ratios.

This integrative approach reveals key environmental drivers of productivity, highlights the role of phytoplankton photophysiology in carbon cycling, and underscores the importance of terrestrial inputs and marine production on coastal and oceanic biogeochemistry. It also provides critical insights for improving ecological models, which are essential for predicting climate change impacts, particularly in river-influenced regions like the Amazon Plume.