Time series analysis of Calanus finmarchicus and Centropages typicus abundance with respect to the converging time frequencies in multiple climate mechanisms in the Gulf of Maine.

Catherine Nowakowski, University of Rhode Island Narragansett Bay, Graduate School of Oceanography, Narragansett, RI, United States, Karen Stamieszkin, Virginia Institute of Marine Science, Gloucester Point, United States, Nicholas Record, Bigelow Lab for Ocean Sciences, Tandy Center for Ocean Forecasting, East Boothbay, United States and Kelton McMahon, University of Rhode Island, Graduate School of Oceanography, Narragansett, United States
Abstract:
Understanding the mechanisms of climate-driven ecosystem change is a major challenge in oceanography due to the often non-linear nature of large- and small-scale ocean processes that cover multiple time scales to drive ecosystem conditions. The Gulf of Maine has been identified as an ideal case study for exploring the climatic and oceanographic drivers of multi-decadal ecosystem change due to the rapid warming it has undergone in recent years -surface waters in the Gulf of Maine have warmed faster than 99.9% of the world’s oceans- and the interaction of major ocean currents in its system. At multiple timescales, climate phenomena like the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning Circulation (AMOC) have been linked to both changes in Gulf Stream and Labrador Current dynamics as well as temperature, salinity, and nutrient availability. These bottom up forcings are hypothesized to have a major impact on zooplankton community composition and abundance, which in turn has major impacts on Gulf of Maine food web structure, biogeochemical cycling, and export production. To unweave these complex interfaces, this study examined climatic and oceanographic drivers of population dynamics in two critical zooplankton species, large-bodied, sub-arctic Calanus finmarchicus and small-bodied, temperate Centropages typicus. We used an autoregressive integrated moving average (ARIMA) multivariate time series analysis to investigate the response in species abundance to climate indicators on frequencies such as: decadal (NAO), multidecadal (Atlantic Multidecadal Oscillation) and long-term warming (Gulf Stream Index and AMOC). We found that this approach better constrained links in key environmental variables, such as how bottom temperature and salinity drive zooplankton abundance. Our model identified important lags between climate indices and zooplankton abundance that we used to examine the shifts between dominant climate forcings each decade on zooplankton abundance. Application of this method provides insight into variations in climate-driven ecosystem change and informs our understating of how ecology in the Gulf of Maine is expected to change in the face of global warming.