Zooplankton population variability in a warming ocean: Modeling spatiotemporal patterns and drivers within a dynamic shelf ecosystem

Climate change is rapidly altering marine ecosystems, so it is imperative that we develop the necessary statistical tools to understand, model, and predict these impacts. In the warming waters of the Gulf of Maine in the Northeast U.S. Shelf (NES), the copepod Calanus finmarchicus plays a critical role in the food web by mediating the flow of carbon to higher trophic levels and providing a valuable food source for commercially and ecologically important fish and large mammals. This thesis develops data-driven statistical models to shed light on the patterns and mechanisms influencing the population dynamics of this indispensable species in the subarctic North Atlantic. First, spatial modeling of C. finmarchicus synchrony reveals that populations in the well-connected NES ecosystem are highly variable and predominantly driven by local habitat heterogeneity rather than region-wide environmental conditions. Notably, populations connected via advection and experiencing synchronous temperature conditions are not necessarily synchronized, illustrating the influence of internal production. Furthermore, modeling the temporal dynamics of C. finmarchicus shows how shifting phenological events, particularly the timing of the annual phytoplankton bloom in the Gulf of Maine, impacts population dynamics in the inner basins throughout the year. Early bloom initiation leads to higher spring abundance, which consequently leads to a decline in fall populations due to density-dependent predation pressure. Finally, through the detection of dynamic interactions, we find that C. finmarchicus trophic structure changes both seasonally and spatially, which highlights the complexity of zooplankton population responses to biotic drivers and the need to take a highly-resolved, spatiotemporal approach to modeling population dynamics. Thus, this thesis contributes to our understanding of a foundational zooplankton species in the highly dynamic Northwest Atlantic shelf ecosystem, offering a transferable empirical template for other species of interest to better understand population dynamics and community function in the wake of climate change.

Grantor dc:publisher

Massachusetts Institute of Technology and Woods Hole Oceanographic Institution

Year dc:date.issued

2025

Author dc:creator

• Honda, Isabel A.

Advisor dc:contributor.advisor

• Ji, Rubao

• Population dynamics
• Statistical modeling
• Northeast U. S. Shelf

DOI

10.1575/1912/72184

OAI identifier oai:identifier

oai:darchive.mblwhoilibrary.org:1912/72184