Is Oligotrophy an Equalizing Factor Driving Microplankton Species Functional Diversity Within Agulhas Rings?

Abstract

From the southwestern termination of the Agulhas current, anticyclonic eddies are emitted and drift across the South Atlantic Ocean. This study is based on a FORSA (Following Ocean Rings in the South Atlantic) oceanographic cruise, from Cape Town (South AFRica) to Arraial do Cabo (Brazil) in June 2015, during which three eddies of different ages (E1, 7 months; E3, 11 months; E5, 24 months) from the Agulhas current were sampled for microplankton identification and determination of functional traits. The stations where sampling occurred at each eddy included a control outside the eddy and three stations inside the eddy—border, midway (between the border and center), and center (identified through satellite images of sea level anomaly—SLA). Functional traits were determined based on microscopic observations and consultation of the literature. An evident decay in the Agulhas eddies toward the west was observed, and each eddy proved to be different. E1 represented a younger and more robust structure. At the same time, the other eddies, E3 and E5, were more alike with similar physical, chemical, and ecological characteristics and almost the same indices values of functional diversity, demonstrating that although their species compositions were different, the strategies used by the species were the same. The most crucial ecological trait for microplankton was nutrition mode. The microplankton contained mainly mixotrophic dinoflagellates and cyanobacteria adapted to oligotrophic conditions. The functional strategy of microplankton did not differ among the eddies and stations, with mixotrophy being the most striking trait. Therefore, the older eddies’ microplankton community fits the neutrality theory, whereby species perform similar ecological functions, and the younger eddy fits in the niche complementarity. Even with the species composition being different in each eddy and/or within the same eddy, the functional strategy was the same, with scarce resources and species selected that best use any source of nutrients or use evolutionary advantages to live in an oligotrophic environment.

Temporal and spatial variability of constitutive mixotroph abundance and proportion

“…Furthermore, certain species might be biased against fluorescently labeled particles, while others may be overly biased towards them (Sanders and Gast 2012 , Wilken et al 2019 ). Recent studies have also attempted to estimate mixotroph abundance in publicly available microscopy datasets via taxonomy (Haraguchi et al 2018 , Leles et al 2019 , Cesar-Ribeiro et al 2020 , Schneider et al 2020 , Li et al 2023 , Mitra et al 2023 ). This approach uses available microscopy-based taxonomic data to estimate the abundance and proportion of potential mixotrophs, plankton that have been found to be capable of photoautotrophy and phagotrophy in previous peer-reviewed studies, over large temporal and spatial scales.…”

Prochlorococcus and Synechococcus marine cyanobacteria: a scientometrics review

“…Prochlorococcus and Synechococcus are among the most abundant taxa in the collective photosynthetic activity of cyanobacteria and occupy deeper areas of the water column (Veldhuis & Kraay 2000). These two genera are generally found together, with their depth distributions differing in absolute concentrations and vertical extension, except in homogeneous water columns (Li et al 1992, Campbell & Vaulot 1993, Veldhuis & Kraay 1993, Cesar-Ribeiro et al 2020.…”

Temporal and spatial variability of phytoplankton and mixotrophs in a temperate estuary

“…Fluorescently labeled bacteria and fluorescent microspheres have long been used to estimate mixotroph abundance and ingestion rates, but research shows that these methods underestimate true abundance (Anderson et al 2017, Li et al 2021. More recently, a few studies have identified potential mixotrophs in field samples via taxonomy, referring to phototrophs that have been found to consume prey in previous experiments (Haraguchi et al 2018, Leles et al 2019, Cesar-Ribeiro et al 2020, Schneider et al 2020. For example, Schneider et al (2020) used microscopy-based taxonomic information from a long-term North Sea dataset to link the occurrence and abundance of potential mixotrophs with abiotic conditions (offshore versus estuarine).…”