Virginia Maria Tavano

Shifts in the dominance between diatoms and cryptophytes during three late summers in the Bransfield Strait (Antarctic Peninsula)

Recent global warming reduces surface water salinity around the Antarctic Peninsula as a result of the glacial meltwater runoff, which increases the occurrence and abundance of certain phytoplankton groups, such as cryptophytes. The dominance of this particular group over diatoms affects grazers, such as Antarctic krill, which preferentially feed on diatoms. Using three late summer data sets from the Bransfield Strait (2008–2010), we observed variations in the dominant phytoplankton groups determined by HPLC/CHEMTAX pigment analysis and confirmed by microscopy. Results indicate that the dominance of diatoms, particularly in 2008 and 2009, was associated with a deeper upper mixed layer (UML), higher salinity and warmer sea surface temperature. In contrast, cryptophytes, which were dominant in 2010, were associated with a shallower UML, lower salinity and colder sea surface temperatures. The low diatom biomass observed in the summer of 2010 was associated with high nutrient concentration, particularly silicate, and low chlorophyll a (summer monthly average calculated from satellite images). The interannual variability here observed suggests a delayed seasonal succession cycle of phytoplankton in the summer of 2010 associated with a cold summer and a late ice retreat process in the region. This successional delay resulted in a notable decrease of primary producers’ biomass, which is likely to have impacted regional food web interactions. This study demonstrates the susceptibility of the Antarctic phytoplankton community structure to air temperature, which directly influences the timing of ice melting and consequently the magnitude of primary production and succession pattern of phytoplankton groups.

Trichodesmium latitudinal distribution on the shelf break in the southwestern Atlantic Ocean during spring and autumn

We report Trichodesmium slicks in the South Atlantic associated with fronts produced by the southward displacement of the Brazil Current. For the first time, a relatively high spatial sampling grid of trichomes density is shown over an undersampled region with regard to Trichodesmium. In this study, the distributions of Trichodesmium along the southeastern Brazilian continental shelf break were characterized during four oceanographic cruises and related to seawater temperature, upper layer nutrient concentrations and wind dynamics. Meridional changes in the densities of trichomes followed an expected trend with higher (lower) values found in warmer (colder) and more saline (less saline) water masses. Between 23° and 28°S, large accumulations of trichomes were associated with high temperature, increased phosphate concentrations (>0.08 μM), nitrogen below 2.4 μM, and low wind speeds (<11 m s−1). Maximum densities of 212.6 × 105 trichomes L−1, which are considerably larger than those reported in other studies in subtropical oceans, occurred at stations showing weak water column stability and higher phosphate levels over the upper 25 m. We suggest that shelf break dynamics, which drive and modulate the intensity of the shelf break upwelling, as well as wind divergence at spatial scales of approximately 600 km2, associated with mesoscale activities, may favor Trichodesmium growth and accumulation. On the other hand, Trichodesmium densities were low at latitudes between 28° and 33°S, likely due to either or both the lowest sea surface temperatures and/or out-competition by the faster-growing nondiazotrophs.

Pigment-based chemotaxonomy of phytoplankton in the Patos Lagoon estuary (Brazil) and adjacent coast

ABSTRACT The composition and distribution of phytoplankton assemblages were studied monthly at two sites in the Patos Lagoon estuary and at one site on the adjacent coast over three years (May 2012–April 2015). Samples were collected for microscopic examination and high-performance-liquid-chromatography pigment analysis. The pigment data were analysed using CHEMTAX software to estimate the contribution of different taxonomic groups to total chlorophyll a (Chl a). Phytoplankton assemblages were generally dominated by diatoms, which contributed, on average, 51% of the total Chl a, especially at the Cassino Beach surf zone, where Asterionellopsis guyunusae was the main species contributing to the high diatom-associated biomass. Cyanobacteria appeared as an important group at the lagoon’s mouth station, contributing, on average, 37% of the total Chl a. Cryptophytes, chlorophytes, prasinophytes and dinoflagellates were less important and contributed, on average, 13, 7, 5 and 3%, respectively, of the total phytoplankton biomass in the region. A good correlation was found between microscopy counts and CHEMTAX biomass estimates for most phytoplankton groups. The relationship, however, was poor for cyanobacteria and green algae, where the pigment-based approach estimated relatively higher biomasses. This discrepancy may be related to either the presence of plant/algae detritus in the samples (captured by the pigment method) and/or an underestimation by the microscopic method. Despite some differences, the pigment-based method successfully described the overall phytoplankton community pattern during the study period. Canonical Correspondence Analysis showed that temperature, salinity and dissolved inorganic nutrients are important driving forces of the observed variation in the phytoplankton community.

Shifts in microphytoplankton species and cell size at Admiralty Bay, Antarctica

Abstract Phytoplankton (>15 µm) was investigated in three shallow coastal areas at Admiralty Bay (AB) between the summers of 2002–03 and 2008–09. Phytoplankton abundance was low (103 cells l-1) and, over time, the prevailing cell size decreased due to a shift in phytoplankton dominant species from diatoms to dinoflagellates. In situ and remote sensing data showed that oscillations in sea surface temperature, precipitation, ice formation/melting, irradiance (cloud cover) and bottom circulation (indexed by the Antarctic Oscillation Index; AAO) were shown to govern the structure of the phytoplankton. Under negative AAO, diatoms prevailed, with the dominance of large (>80 µm) benthic diatoms (e.g. Corethron pennatum and Navicula directa) in periods of low production (102 cells l-1 in 2002–03), and medium-sized (31–80 µm) centrics (e.g. Thalassiosira spp. and Stellarima microtrias) when the abundance was higher (104 cells l-1 in 2003–04). Conversely, positive AAO led to the co-dominance of dinoflagellates and planktonic diatoms (e.g. Pseudo-nitzschia spp.) in the summers of 2007–08 and 2008–09. These results suggest that the AAO can be a good predictor of phytoplankton in coastal areas around the western Antarctic Peninsula, and may help our understanding of changes in other trophic levels of the food web.

Overview on Primary Production in the Southwestern Atlantic

Photosynthesis is the fundamental process by which autotrophs produce organic matter to sustain the biosphere using basic elements (i.e., CO2 and H2O) and solar irradiance as energy source. Marine phytoplankton provides near half of the global primary production (PP), being at the base of most marine trophic webs and playing an important role in the cycling of atmospheric CO2. Therefore, it is crucial to estimate and understand the relationships between environmental conditions and PP rates in the global ocean. There are scarce field estimations of PP in the southern hemisphere and in the Southwestern Atlantic in particular. Hence, global estimates are generally made using indirect methods, such as satellite or biogeochemical models, which should be validated and adjusted with field data to produce reliable results.

Supervised Microalgae Classification in Imbalanced Dataset

Microalgae are unicellular organisms that have physical characteristics such as size, shape or even the present structures. Classifying them manually may require great effort from experts since thousands of microalgae can be found in a small sample of water. Furthermore, the manual classification is not a trivial operation. The results show an important improvement in the classification quality when cost matrix and sampling methods are associated with supervised algorithm.