Quantifying spatial and temporal scales of phytoplankton variability in the Sub-Antarctic Ocean using a high-resolution glider dataset - Little, Hazel Jean (Department of Oceanography, 2017)
Phytoplankton in the Sub-Antarctic Southern Ocean have a distinct seasonal cycle, which is highly variable in both space and time. The seasonal and spatial distribution of chlorophyll can be attributed to the complex nature of the physical and biogeochemical factors controlling phytoplankton production. Studies show that high-resolution sampling is required to understand variability in phytoplankton distribution and primary production. In this study, high-resolution glider data sampled in the Atlantic Sub-Antarctic Zone are used to characterise the scales of phytoplankton variability. Continuous glider data provide a novel way to assess phytoplankton variability at small time and space scales (meso- to submesoscale), especially in an area that has a lack of continuous measurements, which are necessary for addressing climate related questions. Temporal variability of phytoplankton was investigated using Empirical Mode Decomposition of surface chlorophyll-a concentrations collected from a Seaglider over a period of 5.5 months (25 September 2012 to 15 February 2013). This study found that during spring, chlorophyll-a concentrations were dominated by small scale daily fluctuations as well as by the rising seasonal ramp due to seasonal stratification. The removal of these signals revealed that the chlorophylla variability was dominated by submesoscales. In spring, phytoplankton blooms occurred as a result of features that shoaled the mixed layer depth when the wind stress weakened, elevating light conditions for short periods and allowing increased growth. In summer phytoplankton blooms were found to occur at submesoscales periods as well. This variability was found to be driven by synoptic storms varying the strength of the wind stress and consequently the mixed layer depth (that alters the nutrient and light environment). Additionally, through reconstructing the time series through subsampling at the dominant signals, this study found that in order to accurately resolve and characterise the multiseasonal variability of phytoplankton, chlorophyll needs to be sampled at high frequencies (<10 days). Spatial variability was investigated using daily MODIS ocean colour and sea surface temperature images coincident with the glider track. Spatial variability was characterised by the variance calculated at different length scales. Spatial analysis found that phytoplankton were patchier in both spring and summer when compared to sea surface temperature, at all length scales and that a greater variance was contained at small scales. There was also a greater variance in summer chlorophyll-a compared to spring due to higher maximum biomass. Further spatial analysis compared satellite spatial variance with glider measurements at the same length scale (70 km). This study found that a third of the variability found by the glider was caused by spatial patchiness, while the remainder could be contributed by local growth. These dominant meso- and submesoscale changes in chlorophyll-a at both temporal and spatial scales, highlights the need to resolve for both meso- to submesoscales in order to accurately reflect phytoplankton seasonal variability and ultimately to understand the impact of phytoplankton variability on carbon flux.