Diel, Seasonal, and Interannual Variability in Abundance of Major Mesozooplankton Taxa in the Sargasso Sea as Related to Changing Environmental Parameters

Temporal changes in mesozooplankton community structure affect planktonic food web interactions and biogeochemical cycling. Epipelagic mesozooplankton biomass in the Sargasso Sea has increased over the last two decades, with a related increase in zooplankton-mediated carbon export. Unknown, however, is what are the patterns and variability at different temporal scales (diel, seasonal, and interannual) in abundance of each major zooplankton taxon, and how do these patterns relate to physical and other environmental changes? We enumerated major taxa of mesozooplankton collected from monthly day and night net tows in the epipelagic zone at the Bermuda Atlantic Time-series Study (BATS) site in the Sargasso Sea from 1999 to 2010. Abundances of each taxon were determined using a ZooScan optical imaging system and microscopy. Generalized Linear Models (GLMs) were used to determine what environmental parameters best explain abundance of major taxa. We used annual averages to consider broader patterns. Zooplankton taxa with the most pronounced diel vertical migration (i.e., night:day ratio, N:D, >>1) included Limacina spp. pteropods (N:D=2.02), euphausiids (1.93), calanoid copepods (1.34), and heteropods (1.34). Taxa with a pronounced spring abundance peak included chaetognaths, larvaceans, and Limacina spp. pteropods, while harpacticoid copepods peaked in late summer, and calanoid copepods in both spring and summer. Environmental variables affecting abundance differed amongst taxa. For example, calanoid copepod density was highly influenced by the abundance of a major predator– chaetognaths. Multi-year densities of calanoid copepods and ostracods both increased with increasing Water Column Stratification Index and the Atlantic Multidecadal Oscillation (AMO) index, indicating warmer sea surface temperatures are favorable for these taxa. We discuss how these temporal patterns at different scales help predict effects of global climate change on the zooplankton community.