Annual cycle of phytoplankton, protozoa and diatom species from Scotia Bay (South Orkney Islands, Antarctica): Community structure prior to, during and after an anomalously low sea ice year

Abstract

Deepening the knowledge on Antarctic coastal plankton and its links with environmental conditions is essential to understand the role of these organisms in the carbon and energy flow, and to detect and predict impacts of climate change. This study addresses for the first time the seasonal succession (February 2016 to April 2017) of the phytoplanktonic and protozoan communities of Scotia Bay (Laurie Island, South Orkney Islands) and covers the period of the largest negative anomaly in Antarctic sea ice coverage in the last 40 years and the lowest sea ice duration in the bay since 2012. The density and biomass of diatoms, dinoflagellates, silicoflagellates, pigmented and non-pigmented nanoflagellates, and ciliates were assessed in relation with physico-chemical and meteorological variables. Prevailing groups were diatoms in spring-summer, and nanoflagellates (pigmented and non-pigmented) and ciliates in autumn–winter. A marked contrast was found between February 2016 and February 2017 in coincidence with a time shift in the sea ice breakout (December 2015 vs. October 2016): February 2016 was dominated by diatoms (∼250 µgC l−1), whereas the bulk of biomass in February 2017 was represented by dinoflagellates (∼9 µgC l−1) and preceded in January by a massive bloom of the diatoms Odontella weissflogii, Eucampia antarctica, Thalassiosira tumida and Chaetoceros socialis (90% of total diatom biomass: ∼687 µgC l−1). The bloom occurred in association with an event of intense wind followed by days of relative calm. The strong 2015/2016 El Niño and a positive SAM coincided with a late 2015 sea ice breakout and a short productive period in Scotia Bay (January-March 2016), while the early breakout in 2016 occurred during a negative SAM and lead to a more extensive productive period (October 2016-January 2017). Future studies should cover interannual scales in order to understand feedbacks in the structure of microbial communities and environmental forces acting in normal and atypical conditions.