Higher biotic than abiotic natural variability of the plankton ecosystem revealed by a time series along a subantarctic transect

Abstract

Climate projections for the end of the century predict changes in the mean and also the variability of physical parameters critical to marine ecosystems, in particular at high latitudes. Here, we aimed to study the natural variability of major components of the pelagic ecosystem along a subantarctic zonal transect (∼55° S) from coastal waters of the Beagle Channel to the open sea over the Marine Protected Area (MPA) Namuncurá-Burdwood Bank. We used a multi-year dataset, unprecedented for this region, comprising six oceanographic surveys from 2014 to 2018. The dataset includes water temperature, salinity, nitrogen and phosphate concentrations, and abundances for heterotrophic and autotrophic picoplankton and viral populations. We explored three dimensions of the natural variability of the ecosystem: regional (between marine sectors, Coast-Shelf versus Burdwood Bank), local (within marine sectors at each campaign), and temporal (between campaigns, which comprised inter- and intra-annual variability). Biological components including viruses accounted for a greater variability compared with physicochemical parameters. Coast-shelf waters and open sea differed in the temporal variability of the phytoplankton community and most of the environmental parameters, whereas the variability of heterotrophic bacteria was similar between regions. Local effects (i.e., effects at a small spatial scale) prevailed as the main source of variability for all groups of the picoplankton (including viruses), and regional effects for the environmental components. Temporal effects on natural variability were relatively high and even among components with minima for picoeukaryotes and salinity. The observed impacts of climate change are expected to differ among ecosystem components and dimensions, with some impacts being more noticeable in the frequency of extreme events, while others in the mean. Thus, understanding these baseline behaviors could improve management and monitoring strategies.